scholarly journals On-Line Diagnosis and Fault State Classification Method of Photovoltaic Plant

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4584
Author(s):  
Jun-Hyun Shin ◽  
Jin-O Kim
Keyword(s):  
Output Power ◽  
Power Plants ◽  
Plant Performance ◽  
Performance Ratio ◽  
Energy Output ◽  
Support Vector ◽  
Linear Regression Method ◽  
Error Matrix ◽  
On Line ◽  
Fault State

This paper presents an on-line diagnosis method for large photovoltaic (PV) power plants by using a machine learning algorithm. Most renewable energy output power is decreased due to the lack of management tools and the skills of maintenance engineers. Additionally, many photovoltaic power plants have a long down-time due to the absence of a monitoring system and their distance from the city. The IEC 61724-1 standard is a Performance Ratio (PR) index that evaluates the PV power plant performance and reliability. However, the PR index has a low recognition rate of the fault state in conditions of low irradiation and bad weather. This paper presents a weather-corrected index, linear regression method, temperature correction equation, estimation error matrix, clearness index and proposed variable index, as well as a one-class Support Vector Machine (SVM) method and a kernel technique to classify the fault state and anomaly output power of PV plants.

A Case Study of Optimizing Combined Cycle Performance at Kalaeloa

2009 ◽  
Author(s):  
Helmer Andersen
Keyword(s):  
Power Plants ◽  
Performance Monitoring ◽  
Combined Cycle ◽  
Plant Performance ◽  
Operational Performance ◽  
Cycle Performance ◽  
Monitoring Tools ◽  
Online Performance Monitoring ◽  
On Line

Fuel is by far the largest expenditure for energy production for most power plants. New tools for on-line performance monitoring have been developed for reducing fuel consumption while at the same time optimizing operational performance. This paper highlights a case study where an online performance-monitoring tool was employed to continually evaluate plant performance at the Kalaeloa Combined Cycle Power Plant. Justification for investment in performance monitoring tools is presented. Additionally the influence of various loss parameters on the cycle performance is analyzed with examples. Thus, demonstrating the potential savings achieved by identifying and correcting the losses typically occurring from deficiencies in high impact component performance.

scholarly journals Performance Evaluation of 100kWp Roof-top Grid-connected PV System installed in Northern India

2019 ◽  
Vol 8 (3) ◽  
pp. 8441-8444 ◽  
Keyword(s):  
Degradation Rate ◽  
Capacity Utilization ◽  
Plant Performance ◽  
Performance Ratio ◽  
Energy Output ◽  
System Efficiency ◽  
Pv System ◽  
Utilization Factor ◽  
Northern India ◽  
Efficiency Performance

The performance of 100 kWp roof-top grid-connected PV system was evaluated. The plant was installed at PGDM building in Sharda University, Greater Noida in northern India. The plant was monitored from March 2018 to February 2019. Performance parameters such as system efficiency, performance ratio, capacity utilization factor, and degradation rate were obtained. The plant performance result was compared with the estimated results obtained from SAM and PVsyst software. The total annual energy output was found to be 16426 kWh. The annual average system efficiency and capacity utilization factor of the plant was found to be 15.62 % and 14.72 % respectively. The annual performance ratio and annual degradation rate were found to be 76% and 1.28%/year respectively. The annual performance ratio obtained from SAM and PVsyst was found to be 78% and 82% respectively. It was noticed that the measured performance ratio was highly relative with the one obtained from SAM software.

scholarly journals Performance assessment of a 619kW photovoltaic power plant in the northeast of peninsular Malaysia

2020 ◽  
Vol 20 (1) ◽  
pp. 9
Author(s):  
M. Nirrmahl Raj ◽  
Jagadeesh Pasupuleti
Keyword(s):  
Power Plants ◽  
Peninsular Malaysia ◽  
Performance Criteria ◽  
Plant Performance ◽  
Performance Ratio ◽  
Generation Model ◽  
Future Studies ◽  
Performance Requirements ◽  
One Year ◽  
East Asia Region

<span lang="EN-GB">Photovoltaic (PV) power plants are becoming widely implemented and in larger scale around the world. Understanding performance criteria is crucial in the benchmark of PV plants and ascertaining performance requirements during both design and operational stage of a PV plant. Performance Ratio (PR) and Capacity Factor (CF) are two generally accepted benchmarks for the assessment of a grid connected PV plant. However, within the South East Asia region, and especially within Malaysia, there is a lack of compilation and benchmark for the PR and CF values of existing and operational PV plants. This lack of data is disadvantageous for the designing and assessment of performance of any PV plants in the area. Thus, the focus of this study is to assess the PR and CF performance a 619kW PV plant in the Northeast of Peninsular Malaysia, with the ultimate goal of proposing a standard. From the continuous operation of the said PV plant for the duration of one year, the plant energy production has been obtained and is compared with the simulated energy generation model. Based on the comparison, the plant is determined to be operating with PR value of 0.77 and CF value of 12%. The plant is evaluated to be operating within benchmark values</span><span lang="EN-GB">. These values not only verify the performance of the studied PV plant, they also present a form of comparison </span><span lang="EN-GB">for future studies.</span>

scholarly journals Preliminary Evaluation of a Rooftop Grid-Connected Photovoltaic System Installation under the Climatic Conditions of Texas (USA)

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 586
Author(s):  
Fadhil Y. Al-Aboosi ◽  
Abdullah F. Al-Aboosi
Keyword(s):  
Power Plants ◽  
Negative Impact ◽  
Photovoltaic System ◽  
Performance Ratio ◽  
Energy Output ◽  
Preliminary Evaluation ◽  
Solar Pv ◽  
Energy Potential ◽  
Pv System ◽  
Pv Systems

Solar photovoltaic (PV) systems have demonstrated growing competitiveness as a viable alternative to fossil fuel-based power plants to mitigate the negative impact of fossil energy sources on the environment. Notwithstanding, solar PV technology has not made yet a meaningful contribution in most countries globally. This study aims to encourage the adoption of solar PV systems on rooftop buildings in countries which have a good solar energy potential, and even if they are oil or gas producers, based on the obtained results of a proposed PV system. The performance of a rooftop grid-tied 3360 kWp PV system was analyzed by considering technical, economic, and environmental criteria, solar irradiance intensity, two modes of single-axis tracking, shadow effect, PV cell temperature impact on system efficiency, and Texas A&M University as a case study. The evaluated parameters of the proposed system include energy output, array yield, final yield, array and system losses, capacity factor, performance ratio, return on investment, payback period, Levelized cost of energy, and carbon emission. According to the overall performance results of the proposed PV system, it is found to be a technically, economically, and environmentally feasible solution for electricity generation and would play a significant role in the future energy mix of Texas.

scholarly journals Why Can Simple Operation and Maintenance (O&M) Practices in Large-Scale Grid-Connected PV Power Plants Play a Key Role in Improving Its Energy Output?

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3798
Author(s):  
Hamid Iftikhar ◽  
Eduardo Sarquis ◽  
P. J. Costa Branco
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Field Data ◽  
Large Scale ◽  
Low Cost ◽  
Plant Performance ◽  
Energy Output ◽  
Weather Data ◽  
Real Field ◽  
Operation And Maintenance

Existing megawatt-scale photovoltaic (PV) power plant producers must understand that simple and low-cost Operation and Maintenance (O&M) practices, even executed by their own personal and supported by a comparison of field data with simulated ones, play a key role in improving the energy outputs of the plant. Based on a currently operating 18 MW PV plant located in an under-developing South-Asia country, we show in this paper that comparing real field data collected with simulated results allows a central vision concerning plant underperformance and valuable indications about the most important predictive maintenances actions for the plant in analysis. Simulations using the globally recognized software PVSyst were first performed to attest to the overall power plant performance. Then, its energy output was predicted using existing ground weather data located at the power plant. Compared with the actual plant’s annual energy output, it was found that it was underperforming by −4.13%, leading to a potential monetary loss of almost 175,000 (EUR)/year. Besides, an analysis of the O&M power plant reports was performed and compared to the best global practices. It was assessed that the tracker systems’ major issues are the forerunner of the most significant PV power plant underperformance. In addition, issues in inverters and combiner boxes were also reported, leading to internal shutdowns. In this case, predictive maintenance and automated plant diagnosis with a bottom-up approach using low-cost data acquisition and processing systems, starting from the strings level, were recommended.

scholarly journals Performance Evaluation of 780 Wp Rooftop Solar PV Power Backup System in Western Kenya

2021 ◽  
pp. 1-9
Author(s):  
Wilkins K. Cheruiyot ◽  
Joel K. Tonui ◽  
Samuel C. Limo
Keyword(s):  
Performance Evaluation ◽  
Solar Radiation ◽  
Output Power ◽  
Operating Conditions ◽  
Performance Ratio ◽  
Energy Output ◽  
Pv System ◽  
Western Kenya ◽  
Pv Array ◽  
Backup System

Aim: This study aimed to carry out performance analysis of a 780 Wp PV power backup system installed at a learning institution in Western. Study design: To achieve this goal, site solar radiation received, ambient temperatures, dc current and dc voltages were measured in order to carry out performance evaluation of the PV backup system. Place and Duration of Study: Department of electronics and electrical, Kaiboi Technical Training Institute in Nandi County, western Kenya was studied, between January 2020 and December 2020. Methodology: Performance of any PV system depends on the operating conditions (solar radiation, ambient/module temperature, etc.) available at the site (geolocation dependent), installation (tilt and orientation) of the arrays, and finally proper system sizing (PV array, battery, BOS). In this paper, standard performance parameters reported in literature were utilized to evaluate the performance of the studied PV backup system. The array comprises of four panels interconnected in series/parallel to produce an output power rating of 780 W. A Pyranometer was mounted on the plane of array (POA) to measure solar radiation intercepted by the PV array where daily data were acquired at an interval of five minutes. I-v data were also recorded. Different literature was reviewed to identify the way to do this work. Results: Based on the performance of the studied PV system, results obtained show that annual effective energy output is 3412.94 kWh, array efficiency range between 11.6% to 14.1% depending on amount of solar radiation, array yield of 4.88 kWh/kW, reference yield of 5.5 kWh/kW, annual average performance ratio of 76.3% and average array capture losses of 0.52 kWh/kW. Conclusion: It found that the PV backup system need ~5-6 hours to operate at the array’s rated output power, and that the PV backup system performance is adequate with regard to yield and performance ratios.

Application of On-Line Optimization Technology to Plant Operation

2000 ◽  
Author(s):  
Rodney R. Gay
Keyword(s):  
Power Generation ◽  
Power Plant ◽  
Gas Turbine ◽  
Power Plants ◽  
Heat Rate ◽  
Combined Cycle ◽  
Plant Performance ◽  
Plant Operation ◽  
Budget Analysis ◽  
On Line

Traditionally optimization has been thought of as a technology to set power plant controllable parameters (i.e. gas turbine power levels, duct burner fuel flows, auxiliary boiler fuel flows or bypass/letdown flows) so as to maximize plant operations. However, there are additional applications of optimizer technology that may be even more beneficial than simply finding the best control settings for current operation. Most smaller, simpler power plants (such as a single gas turbine in combined cycle operation) perceive little need for on-line optimization, but in fact could benefit significantly from the application of optimizer technology. An optimizer must contain a mathematical model of the power plant performance and of the economic revenue and cost streams associated with the plant. This model can be exercised in the “what-if” mode to supply valuable on-line information to the plant operators. The following quantities can be calculated: Target Heat Rate Correction of Current Plant Operation to Guarantee Conditions Current Power Generation Capacity (Availability) Average Cost of a Megawatt Produced Cost of Last Megawatt Cost of Process Steam Produced Cost of Last Pound of Process Steam Heat Rate Increment Due to Load Change Prediction of Future Power Generation Capability (24 Hour Prediction) Prediction of Future Fuel Consumption (24 Hour Prediction) Impact of Equipment Operational Constraints Impact of Maintenance Actions Plant Budget Analysis Comparison of Various Operational Strategies Over Time Evaluation of Plant Upgrades The paper describes examples of optimizer applications other than the on-line computation of control setting that have provided benefit to plant operators. Actual plant data will be used to illustrate the examples.

scholarly journals An Improved Whale Algorithm for Support Vector Machine Prediction of Photovoltaic Power Generation

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 212
Author(s):  
Yu-Wei Liu ◽  
Huan Feng ◽  
Heng-Yi Li ◽  
Ling-Ling Li
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Output Power ◽  
Input Data ◽  
Support Vector Machine Model ◽  
Weather Conditions ◽  
Clean Energy ◽  
Support Vector ◽  
Machine Model ◽  
Photovoltaic Power

Accurate prediction of photovoltaic power is conducive to the application of clean energy and sustainable development. An improved whale algorithm is proposed to optimize the Support Vector Machine model. The characteristic of the model is that it needs less training data to symmetrically adapt to the prediction conditions of different weather, and has high prediction accuracy in different weather conditions. This study aims to (1) select light intensity, ambient temperature and relative humidity, which are strictly related to photovoltaic output power as the input data; (2) apply wavelet soft threshold denoising to preprocess input data to reduce the noise contained in input data to symmetrically enhance the adaptability of the prediction model in different weather conditions; (3) improve the whale algorithm by using tent chaotic mapping, nonlinear disturbance and differential evolution algorithm; (4) apply the improved whale algorithm to optimize the Support Vector Machine model in order to improve the prediction accuracy of the prediction model. The experiment proves that the short-term prediction model of photovoltaic power based on symmetry concept achieves ideal accuracy in different weather. The systematic method for output power prediction of renewable energy is conductive to reducing the workload of predicting the output power and to promoting the application of clean energy and sustainable development.

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