Solar Photovoltaic Plants

2018 ◽  
Vol 52 (1) ◽  
pp. 85-90 ◽  
Author(s):  
D. S. Strebkov ◽  
A. Kh. Shogenov
Keyword(s):  
Solar Photovoltaic ◽  
Photovoltaic Plants

scholarly journals Evaluating the Curtailment Risk of Non-Firm Utility-Scale Solar Photovoltaic Plants under a Novel Last-In First-Out Principle of Access Interconnection Agreement

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1463
Author(s):  
Kwami Senam A. Sedzro ◽  
Kelsey Horowitz ◽  
Akshay K. Jain ◽  
Fei Ding ◽  
Bryan Palmintier ◽  
...  
Keyword(s):  
Solar Photovoltaic ◽  
Study Results ◽  
Utility Companies ◽  
Access Rights ◽  
Time Series Simulation ◽  
Photovoltaic Plants ◽  
Flexible Generation ◽  
Pv Penetration ◽  
Access Right ◽  
Utility Scale

With the increasing share of distributed energy resources on the electric grid, utility companies are facing significant decisions about infrastructure upgrades. An alternative to extensive and capital-intensive upgrades is to offer non-firm interconnection opportunities to distributed generators, via a coordinated operation of utility scale resources. This paper introduces a novel flexible interconnection option based on the last-in, first-out principles of access aimed at minimizing the unnecessary non-firm generation energy curtailment by balancing access rights and contribution to thermal overloads. Although we focus on solar photovoltaic (PV) plants in this work, the introduced flexible interconnection option applies to any distributed generation technology. The curtailment risk of individual non-firm PV units is evaluated across a range of PV penetration levels in a yearlong quasi-static time-series simulation on a real-world feeder. The results show the importance of the size of the curtailment zone in the curtailment risk distribution among flexible generation units as well as that of the “access right” defined by the order in which PV units connect to the grid. Case study results reveal that, with a proper selection of curtailment radius, utilities can reduce the total curtailment of flexible PV resources by up to more than 45%. Findings show that non-firm PV generators can effectively avoid all thermal limit-related upgrade costs.

scholarly journals Automatic Boundary Extraction for Photovoltaic Plants Using the Deep Learning U-Net Model

2021 ◽  
Vol 11 (14) ◽  
pp. 6524
Author(s):  
Andrés Pérez-González ◽  
Álvaro Jaramillo-Duque ◽  
Juan Bernardo Cano-Quintero
Keyword(s):  
Research Work ◽  
Solar Photovoltaic ◽  
Boundary Extraction ◽  
Pv Systems ◽  
Periodic Maintenance ◽  
Planning Algorithm ◽  
Extraction Processes ◽  
Inspection And Maintenance ◽  
Photovoltaic Plants ◽  
Path Planning Algorithm

Nowadays, the world is in a transition towards renewable energy solar being one of the most promising sources used today. However, Solar Photovoltaic (PV) systems present great challenges for their proper performance such as dirt and environmental conditions that may reduce the output energy of the PV plants. For this reason, inspection and periodic maintenance are essential to extend useful life. The use of unmanned aerial vehicles (UAV) for inspection and maintenance of PV plants favor a timely diagnosis. UAV path planning algorithm over a PV facility is required to better perform this task. Therefore, it is necessary to explore how to extract the boundary of PV facilities with some techniques. This research work focuses on an automatic boundary extraction method of PV plants from imagery using a deep neural network model with a U-net structure. The results obtained were evaluated by comparing them with other reported works. Additionally, to achieve the boundary extraction processes, the standard metrics Intersection over Union (IoU) and the Dice Coefficient (DC) were considered to make a better conclusion among all methods. The experimental results evaluated on the Amir dataset show that the proposed approach can significantly improve the boundary and segmentation performance in the test stage up to 90.42% and 91.42% as calculated by IoU and DC metrics, respectively. Furthermore, the training period was faster. Consequently, it is envisaged that the proposed U-Net model will be an advantage in remote sensing image segmentation.

scholarly journals Assessing the geospatial nature of location-dependent costs in installation of solar photovoltaic plants

2021 ◽  
Vol 7 ◽  
pp. 4882-4894
Author(s):  
Soumya Basu ◽  
Takaya Ogawa ◽  
Hideyuki Okumura ◽  
Keiichi N. Ishihara
Keyword(s):  
Solar Photovoltaic ◽  
Photovoltaic Plants

Failure signature classification in solar photovoltaic plants using RGB images and convolutional neural networks

2020 ◽  
Vol 162 ◽  
pp. 249-256 ◽  
Author(s):  
Alejandro Rico Espinosa ◽  
Michael Bressan ◽  
Luis Felipe Giraldo
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Solar Photovoltaic ◽  
Rgb Images ◽  
Photovoltaic Plants

Floating solar photovoltaic plants in India – A rapid transition to a green energy market and sustainable future

2021 ◽  
pp. 0958305X2110571
Author(s):  
J. Charles Rajesh Kumar ◽  
MA Majid
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Large Scale ◽  
Solar Power ◽  
Green Energy ◽  
Sustainable Growth ◽  
Energy Market ◽  
Solar Photovoltaic ◽  
Sustainable Future ◽  
Photovoltaic Plants

The 18,000 square kilometers of water reservoirs in India can generate 280 GW of solar power through floating solar photovoltaic plants. The cumulative installed capacity of FSPV is 0.0027 GW, and the country plans to add 10 GW of FSPV to the 227 GW renewable energy target of 2022. The FSPV addition is small related to the entire market for solar energy, but each contribution is appreciated in the renewable energy market. FSPV could be a viable alternative for speeding up solar power deployment in the country and meeting its NDC targets. So far, the country has achieved the world's lowest investment cost for a floating solar installation. Despite the lower costs, generalizations are still premature because FSPV is still in its initial stages of market entry. Continuous innovation and timely adoption of innovative ideas and technology will support India in meeting its solar energy goals and progressing toward a more sustainable future. Governments must establish clear and enforceable policies to assist developers in reducing risks and increasing investor confidence in the sector. Economic and financial feasibility are examined, and various difficulties in technology, design, finances, environment, maintenance, and occupational health that impact the FSPV deployment are discussed. Based on the research, effective and comprehensive FSPV policy suggestions are included to support establishing an appropriate market, fostering competition and innovation, and attracting large-scale investment. This paper aims to stimulate interest among various policy developers, energy suppliers, industrial designers, ergonomists, project developers, manufacturers, health and safety professionals, executing agencies, training entities, and investment institutions of the FSPV plant to implement effective governance planning and help them to participate in their ways to assure sustainable growth.

Resource Indicators Used for Solar Photovoltaic Plants in Uzbekistan Part 1

2018 ◽  
Vol 54 (4) ◽  
pp. 273-278 ◽  
Author(s):  
N. R. Avezova ◽  
E. Yu. Rakhimov ◽  
J. O. Izzatillaev
Keyword(s):  
Solar Photovoltaic ◽  
Photovoltaic Plants
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