scholarly journals Relation between Solar PV Power Generation, Inverter Rating and THD

2019 ◽  
Vol 9 (1) ◽  
pp. 4570-4575 ◽  
Keyword(s):  
Power Generation ◽  
Power Quality ◽  
Power Flow ◽  
Distribution Networks ◽  
Solar Pv ◽  
Pv Systems ◽  
Distributed Power Generation ◽  
Pv Generation ◽  
Bidirectional Power Flow ◽  
Pv Power Generation

The increasing threat of global warming call for the policy chances that increase the share of renewable energy-based generation including the integration of solar PV generation in the distribution networks. However, the distribution networks are designed and operated for centralised power generation and unidirectional power flow. The integration of solar PV systems leads to distributed power generation and bidirectional power flow, which results in operation challenges, such as power quality problems. These problems required to be quantified to develop appropriate solutions. Therefore, in this paper, a power quality auditing is conducted for a 50 kVA solar PV power plant and the resultant observations are presented in this paper. The study is conducted for two types of days, which are: (i) weekend day; (ii) weekday. The former type of day has relatively lower demand compared to the later type day. A number of observations are made and they are presented in this paper. Few important observations and conclusions are presented in this paper. The relation among the power generation, harmonics and inverters rating are observed and presented. Moreover, the quantification of voltage dips is also presented in this paper.

scholarly journals Ultra-Short-Term Forecasting of Photo-Voltaic Power via RBF Neural Network

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1717
Author(s):  
Wanxing Ma ◽  
Zhimin Chen ◽  
Qing Zhu
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Smart Grids ◽  
Percentage Error ◽  
Solar Pv ◽  
Short Term ◽  
Forecasting Method ◽  
Photo Voltaic ◽  
Short Term Forecasting ◽  
Pv Power Generation

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.

scholarly journals Nanostructures GaAs Solar Cells

2020 ◽  
Author(s):  
Mohammad Nur E Alam ◽  
Narottam Das
Keyword(s):  
Power Generation ◽  
Solar Cells ◽  
Conversion Efficiency ◽  
Human Mobility ◽  
Incident Light ◽  
Front Surface ◽  
Pv Systems ◽  
Energy Demands ◽  
Power Generation Technology ◽  
Pv Power Generation

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.

scholarly journals Algorithm Study on Improving Application Efficiency of Independent Solar Power Supply System

2016 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Jigang Cao
Keyword(s):  
Power Generation ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Important Means ◽  
Power Point ◽  
Pv Power Generation

<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>

Optimal Penetration of Photovoltaic Systems in Distribution Networks

2013 ◽  
Vol 479-480 ◽  
pp. 590-594
Author(s):  
Wei Lin Hsieh ◽  
Chia Hung Lin ◽  
Chao Shun Chen ◽  
Cheng Ting Hsu ◽  
Chin Ying Ho ◽  
...  
Keyword(s):  
Power Generation ◽  
Solar Energy ◽  
Voltage Control ◽  
Distribution Networks ◽  
Solar Irradiation ◽  
Total Power ◽  
Pv System ◽  
Pv Systems ◽  
Power Injection ◽  
Distribution Feeder

The penetration level of a PV system is often limited due to the violation of voltage variation introduced by the large intermittent power generation. This paper discusses the use of an active power curtailment strategy to reduce PV power injection during peak solar irradiation to prevent voltage violation so that the PV penetration level of a distribution feeder can be increased to fully utilize solar energy. When using the proposed voltage control scheme for limiting PV power injection into the study distribution feeder during high solar irradiation periods, the total power generation and total energy delivered by the PV system over a 1-year period are determined according to the annual duration of solar irradiation. With the proposed voltage control to perform the partial generation rejection of PV systems, the optimal installation capacity of PV systems can be determined by maximizing the net present value of the system so that better cost effectiveness of the PV project and better utilization of solar energy can be obtained.

Efficient Reduction in the Annual Investment Costs in AC Distribution Networks via Optimal Integration of Solar PV Sources Using the Newton Metaheuristic Algorithm

2021 ◽  
Vol 11 (23) ◽  
pp. 11525
Author(s):  
Oscar Danilo Montoya ◽  
Luis Fernando Grisales-Noreña ◽  
Lázaro Alvarado-Barrios ◽  
Andres Arias-Londoño ◽  
Cesar Álvarez-Arroyo
Keyword(s):  
Power Flow ◽  
Fitness Function ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Solar Pv ◽  
Flow Method ◽  
Power Flow Method

This research addresses the problem of the optimal placement and sizing of (PV) sources in medium voltage distribution grids through the application of the recently developed Newton metaheuristic optimization algorithm (NMA). The studied problem is formulated through a mixed-integer nonlinear programming model where the binary variables regard the installation of a PV source in a particular node, and the continuous variables are associated with power generations as well as the voltage magnitudes and angles, among others. To improve the performance of the NMA, we propose the implementation of a discrete–continuous codification where the discrete component deals with the location problem and the continuous component works with the sizing problem of the PV sources. The main advantage of the NMA is that it works based on the first and second derivatives of the fitness function considering an evolution formula that contains its current solution (xit) and the best current solution (xbest), where the former one allows location exploitation and the latter allows the global exploration of the solution space. To evaluate the fitness function and its derivatives, the successive approximation power flow method was implemented, which became the proposed solution strategy in a master–slave optimizer, where the master stage is governed by the NMA and the slave stage corresponds to the power flow method. Numerical results in the IEEE 34- and IEEE 85-bus systems show the effectiveness of the proposed optimization approach to minimize the total annual operative costs of the network when compared to the classical Chu and Beasley genetic algorithm and the MINLP solvers available in the general algebraic modeling system with reductions of 26.89% and 27.60% for each test feeder with respect to the benchmark cases.

scholarly journals Techno-Economic Analysis of a Residential PV-Storage Model in a Distribution Network

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3062 ◽  
Author(s):  
Xiong ◽  
Nour
Keyword(s):  
Energy Storage ◽  
Distribution Networks ◽  
Point Of View ◽  
Local Data ◽  
Pv System ◽  
Battery System ◽  
Pv Systems ◽  
High Penetration ◽  
Harmonic Components ◽  
Pv Generation

The high penetration level of photovoltaic (PV) generation in distribution networks not only brings benefits like carbon savings, but also induces undesirable outcomes, like more harmonic components and voltage fluctuations. Driven by decreasing costs of energy storage, the focus of this paper is to investigate the feasibility of applying energy storage in the grid-connected PV system to mitigate its intermittency. Firstly, to appreciate the functionality of storage, a generic PV-battery-supercapacitor model was simulated in MATLAB/Simulink, and a flat load profile was obtained to enhance predictability from the network management point of view. However, the usage of supercapacitors at the residential level is limited, due to its high startup costs. Secondly, a detailed residential PV-battery model was implemented in the System Advisor Model (SAM) based on local data in Dubai. The optimal sizing of a battery system was determined by assessing two criteria: The number of excursions, and average target power, which are contradictory in optimization process. Statistical indicators show that a properly sized battery system can alleviate network fluctuations. The proposed sizing method can be also applied to other PV-storage systems. Finally, economic studies of PV-battery system demonstrated its competitiveness against standalone PV systems under appropriate tariff incentives.

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