Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

Quiles, Eduardo; Roldán-Blay, Carlos; Escrivá-Escrivá, Guillermo; Roldán-Porta, Carlos

doi:10.3390/su12031274

Cited by 39 publications

(25 citation statements)

References 41 publications

(51 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different sizing methods are used in different applications [41][42][43][44][45][46]. In grid-connected applications, the average energy consumption is generally considered the starting point for building a photovoltaic system for such applications [43].…”

Section: Photovoltaic Systemsmentioning

confidence: 99%

“…A separate bill is provided for photovoltaic generation, or the cost of the utility bill is reduced based on photovoltaic generation during the billing period. In the case of standalone applications, extra capacity is included to even out the energy generation differences on different days, with battery storage integrated with standalone photovoltaic systems [42,43,[45][46][47].…”

Section: Photovoltaic Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

Binduhewa

2021

International Journal of Photoenergy

View full text Add to dashboard Cite

A reliable transportation system is essential for the development of a community. Especially in urban transportation, rail transportation is a faster, more comfortable way to travel for the commuters. These benefits can be valued further when the rail transportation system is with zero emissions. Electric trains can be considered a zero-emission transportation method. However, a rail transportation system operates with net-zero emissions when electricity is generated from zero-emission-based sources. Photovoltaic systems have already been integrated into railway stations and spare land owned by railways to achieve net-zero emissions. Furthermore, medium-voltage DC network and microgrid concepts have been proposed to incorporate more renewable energy sources into railway electrification systems. However, the energy generated from those systems is not enough to realise net-zero emissions, as the power requirements of an urban railway electrification system are high. Accordingly, this article investigates the possibility of implementing a photovoltaic system along the railway tracks to meet the energy demands of an urban railway electrification system so that net-zero emissions can be achieved. Other significant advantages of the proposed photovoltaic system are lower feeder losses due to distributed photovoltaic systems integrated into the railway electrification system, lower conversion losses due to the direct integration of the photovoltaic system into the railway electrification system, and the nonrequirement of additional space to install the photovoltaic system. In this paper, a photovoltaic system capacity sizing algorithm is proposed and presented by considering a railway electrification system, the daily schedule of trains, and historical photovoltaic weather data. This proposed photovoltaic system capacity sizing algorithm was evaluated considering a section of the urban railway network of Sri Lanka and a three-year, 2017-2020, photovoltaic weather data. The results indicated that the potential for photovoltaic generation by installing photovoltaic systems along a railway track is much higher than the requirement, and it is possible to meet the required train scheduling options with proper sizing. Furthermore, in the three-year analysis, it is possible to achieve 90% of the energy required for the railway electrification system with effective train scheduling methods.

show abstract

Section: Photovoltaic Systemsmentioning

confidence: 99%

Section: Photovoltaic Systemsmentioning

confidence: 99%

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

Binduhewa

2021

International Journal of Photoenergy

View full text Add to dashboard Cite

show abstract

“…Due to their suitability for multidimensional spaces, ANNs have been widely used in the solar energy field. A great variety of models have been presented, both for the construction of solar panels [19], and for the field of solar energy modeling in Nigeria [20], stand-alone installations [21], daily local energy radiation forecasting [22], residential stand-alone self-sustainability [23], solar power forecasting [24], 24-h-ahead energy production prediction [25], or global forecasting of energy prediction in Spain [26].…”

Section: Related Workmentioning

confidence: 99%

“…In this way, we provide an abstraction layer to the customer, focused ROI of the installation. In [23], the authors focused on the ROI of the solar installation. However, this ANN was focused on a specific stand-alone installation, while our ANN aims to provide a general method that could be applied to almost any installation as long as their characteristics are provided.…”

Section: Related Workmentioning

confidence: 99%

Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data

et al. 2020

View full text Add to dashboard Cite

With climate change driving an increasingly stronger influence over governments and municipalities, sustainable development, and renewable energy are gaining traction across the globe. This is reflected within the EU 2030 agenda, that envisions a future where there is universal access to affordable, reliable and sustainable energy. One of the challenges to achieve this vision lies on the low reliability of certain renewable sources. While both particulars and public entities try to reach self-sufficiency through sustainable energy generation, it is unclear how much investment is needed to mitigate the unreliability introduced by natural factors such as varying wind speed and daylight across the year. In this sense, a tool that aids predicting the energy output of sustainable sources across the year for a particular location can aid greatly in making sustainable energy investments more efficient. In this paper, we make use of Open Data sources, Internet of Things (IoT) sensors and installations distributed across Europe to create such tool through the application of Artificial Neural Networks. We analyze how the different factors affect the prediction of energy production and how Open Data can be used to predict the expected output of sustainable sources. As a result, we facilitate users the necessary information to decide how much they wish to invest according to the desired energy output for their particular location. Compared to state-of-the-art proposals, our solution provides an abstraction layer focused on energy production, rather that radiation data, and can be trained and tailored for different locations using Open Data. Finally, our tests show that our proposal improves the accuracy of the forecasting, obtaining a lower mean squared error (MSE) of 0.040 compared to an MSE 0.055 from other proposals in the literature.

show abstract

“…Research focuses on developing more durable topologies, reducing the installation and maintenance costs of PV systems. In this sense, Reference [20] presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level.…”

Section: Dc/ac Convertermentioning

confidence: 99%

Leakage Current Reduction in Single-Phase Grid-Connected Inverters—A Review

et al. 2020

View full text Add to dashboard Cite

The rise in renewable energy has increased the use of DC/AC converters, which transform the direct current to alternating current. These devices, generally called inverters, are mainly used as an interface between clean energy and the grid. It is estimated that 21% of the global electricity generation capacity from renewable sources is supplied by photovoltaic systems. In these systems, a transformer to ensure grid isolation is used. Nevertheless, the transformer makes the system expensive, heavy, bulky and reduces its efficiency. Therefore, transformerless schemes are used to eliminate the mentioned disadvantages. One of the main drawbacks of transformerless topologies is the presence of a leakage current between the physical earth of the grid and the parasitic capacitances of the photovoltaic module terminals. The leakage current depends on the value of the parasitic capacitances of the panel and the common-mode voltage. At the same time, the common-mode voltage depends on the modulation strategy used. Therefore, by the manipulation of the modulation technique, is accomplished a decrease in the leakage current. However, the connection standards for photovoltaic inverters establish a maximum total harmonic distortion of 5%. In this paper an analysis of the common-mode voltage and its influence on the value of the leakage current is described. The main topologies and strategies used to reduce the leakage current in transformerless schemes are summarized, highlighting advantages and disadvantages and establishing points of comparison with similar topologies. A comparative table with the most important aspects of each converter is shown based on number of components, modes of operation, type of modulation strategy used, and the leakage current value obtained. It is important to mention that analyzed topologies present a variation of the leakage current between 0 to 180 mA. Finally, the trends, problems, and researches on transformerless grid-connected PV systems are discussed.

show abstract

Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

Cited by 39 publications

References 41 publications

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data

Leakage Current Reduction in Single-Phase Grid-Connected Inverters—A Review

Contact Info

Product

Resources

About