Techno-economic impacts of floating PV power generation for remote coastal regions

2022 ◽  
Vol 51 ◽  
pp. 101930
Author(s):  
Muhammad Nasir Uddin ◽  
Md Multan Biswas ◽  
Shaikh Nuruddin
Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1717
Author(s):  
Wanxing Ma ◽  
Zhimin Chen ◽  
Qing Zhu

With the fast expansion of renewable energy systems during recent years, the stability and quality of smart grids using solar energy have been challenged because of the intermittency and fluctuations. Hence, forecasting photo-voltaic (PV) power generation is essential in facilitating planning and managing electricity generation and distribution. In this paper, the ultra-short-term forecasting method for solar PV power generation is investigated. Subsequently, we proposed a radial basis function (RBF)-based neural network. Additionally, to improve the network generalization ability and reduce the training time, the numbers of hidden layer neurons are limited. The input of neural network is selected as the one with higher Spearman correlation among the predicted power features. The data are normalized and the expansion parameter of RBF neurons are adjusted continuously in order to reduce the calculation errors and improve the forecasting accuracy. Numerous simulations are carried out to evaluate the performance of the proposed forecasting method. The mean absolute percentage error (MAPE) of the testing set is within 10%, which show that the power values of the following 15 min. can be predicted accurately. The simulation results verify that our method shows better performance than other existing works.


2021 ◽  
Vol 11 (2) ◽  
pp. 727 ◽  
Author(s):  
Myeong-Hwan Hwang ◽  
Young-Gon Kim ◽  
Hae-Sol Lee ◽  
Young-Dae Kim ◽  
Hyun-Rok Cha

In recent years, photovoltaic (PV) power generation has attracted considerable attention as a new eco-friendly and renewable energy generation technology. With the recent development of semiconductor manufacturing technologies, PV power generation is gradually increasing. In this paper, we analyze the types of defects that form in PV power generation panels and propose a method for enhancing the productivity and efficiency of PV power stations by determining the defects of aging PV modules based on their temperature, power output, and panel images. The method proposed in the paper allows the replacement of individual panels that are experiencing a malfunction, thereby reducing the output loss of solar power generation plants. The aim is to develop a method that enables users to immediately check the type of failures among the six failure types that frequently occur in aging PV panels—namely, hotspot, panel breakage, connector breakage, busbar breakage, panel cell overheating, and diode failure—based on thermal images by using the failure detection system. By comparing the data acquired in the study with the thermal images of a PV power station, efficiency is increased by detecting solar module faults in deteriorated photovoltaic power plants.


Author(s):  
Cheng-Ting Hsu ◽  
Hung-Ming Huang ◽  
Tsun-Jen Cheng ◽  
Yih-Der Lee ◽  
Yung-Ruei Chang ◽  
...  

Author(s):  
Dongsu Kim ◽  
Heejin Cho ◽  
Rogelio Luck

This study evaluates potential aggregate effects of net-zero energy building (NZEB) implementations on the electrical grid in simulation-based analysis. Many studies have been conducted on how effective NZEB designs can be achieved, however the potential impact of NZEBs have not been explored sufficiently. As significant penetration of NZEBs occurs, the aggregated electricity demand profile of the buildings on the electrical grid would experience dramatic changes. To estimate the impact of NZEBs on the electrical grid, a simulation-based study of an office building with a grid-tied PV power generation system is conducted. This study assumes that net-metering is available for NZEBs such that the excess on-site PV generation can be fed to the electrical grid. The impact of electrical energy storage (EES) within NZEBs on the electrical grid is also considered in this study. Finally, construction weighting factors of the office building type in U.S. climate zones are used to estimate the number of national office buildings. In order to consider the adoption of NZEBs in the future, this study examines scenarios with 20%, 50%, and 100% of the U.S. office building stock are composed of NZEBs. Results show that annual electricity consumption of simulated office buildings in U.S. climate locations includes the range of around 85 kWh/m2-year to 118 kWh/m2-year. Each simulated office building employs around 242 kWp to 387 kWp of maximum power outputs in the installation of on-site PV power systems to enable NZEB balances. On a national scale, the daily on-site PV power generation within NZEBs can cover around 50% to 110% of total daily electricity used in office buildings depending on weather conditions. The peak difference of U.S. electricity demand typically occurs when solar radiation is at its highest. The peak differences from the actual U.S. electricity demand on the representative summer day show 9.8%, 4.9%, and 2.0% at 12 p.m. for 100%, 50%, and 20% of the U.S. NZEB stocks, respectively. Using EES within NZEBs, the peak differences are reduced and shifted from noon to the beginning of the day, including 7.7%, 3.9%, and 1.5% for each percentage U.S. NZEB stock. NZEBs tend to create the significant curtailment of the U.S. electricity demand profile, typically during the middle of the winter day. The percentage differences at a peak point (12 p.m.) are 8.3%, 4.2%, and 1.7% for 100%, 50%, and 20% of the U.S. NZEB stocks, respectively. However, using EES on the representative winter day can flatten curtailed electricity demand curves by shifting the peak difference point to the beginning and the late afternoon of the day. The shifted peak differences show 7.4%, 3.7%, and 1.5% at 9 a.m. for three U.S. NZEB stock scenarios, respectively.


Author(s):  
R.S. Ravi Sankar ◽  
S.V. Jayaram Kumar ◽  
G. Mohan Rao

Now a day‟s, Photo Voltaic (PV) power generation rapidly increasing. This power generation highly depending on the temperature and irradiation. When this power interface with grid through the voltage source inverter with PI controller. Its gains should be updated due to the parametric changes for the better performance. In This Work Fuzzy Controller updates the gains of the proportional integral (PI)s Controller under variable parametric conditions. the gaines of the PI Controller are updated based on the error current and change in error current through the fuzzy controller. The error current in direct and quadrature frame are the Inputs to the PI controller. The PI Controller generates the reference voltage to the pulse width modulation technique. Here reference voltage is compared with the carrier signal to generate the pulses to the 3-Ph Inverter connected to the grid. This controller has given well dynamic response with less steady state error and also given The less THD of the grid current compared to the PI and Fuzzy controller.It Is implemented and verified in MATLAB Simulink.


Author(s):  
Mohammad Nur E Alam ◽  
Narottam Das

At present, the world is now passing a very far different time than normal situation due to the COVID-19 pandemic crisis. The global life-style and human civilization is currently progressing with down-stream that affecting almost every sectors necessary for human civilizations except the current environmental situation. To control the COVID-19 spreading, most of the countries are following lockdown process that reduces human mobility, thus reducing the CO2 emission to the environment. Though the COVID-19 pandemic is a blessing for the present environment, however, the post-COVID world will face a massive thrust of energy and only conventional energy resources may not be enough to mitigate the energy demands. Solar power generation technology mainly the photovoltaic (PV) systems and their advancement can be the leading possibilities to minimize the gap between the power demand and generation. It is now time to think how we can improve the PV power generation in future and the post-COVID world. In this encyclopaedia communication, we report on Nano-technological approach to improve the conversion efficiency of GaAs solar cells. We have designed and optimized several types of nano-structured assemblies that can be implemented to reduce the front surface incident light reflection losses thus can assist to improve the conversion efficiency of GaAs solar cells.


2016 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Jigang Cao

<p class="p1"><span class="s1">With the development of photovoltaic (PV) technologies, applications of photovoltaic have grown rapidly, indicating that the photovoltaic are attractive to produce environmentally benign electricity for diversified purposes. In order to maximize the use of solar energy, this thesis focuses on the PV power generation systems, which includes modeling of PV systems, maximum power point tracking (MPPT) methods for PV arrays. </span><span class="s1">Maximum Power Point Tracking (MPPT) method is an important means to improve the system efficiency of PV power generation system. MPPT theory and various MPPT algorithms are introduced in the literature. Based on those researches, this thesis proposes a novel implementation of an adaptive duty cycle P&amp;O algorithm that can reduce the main drawbacks commonly related to the traditional P&amp;O method.</span></p>


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