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 Clustering time series applied to energy markets

2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Cornelia Krome ◽  
Jan Höft ◽  
Volker Sander
Keyword(s):  
Time Series ◽  
Power Plant ◽  
Electricity Market ◽  
Power Plants ◽  
Large Scale ◽  
Energy Systems ◽  
Weather Data ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Virtual Power Plants

Abstract In Germany and many other countries the energy market has been subject to significant changes. Instead of only a few large-scale producers that serve aggregated consumers, a shift towards regenerative energy sources is taking place. Energy systems are increasingly being made more flexible by decentralised producers and storage facilities, i.e. many consumers are also producers. The aggregation of producers form another type of power plants: a virtual power plant. On the basis of aggregated production and consumption, virtual power plants try to make decisions under the conditions of the electricity market or the grid condition. They are influenced by many different aspects. These include the current feed-in, weather data, or the demands of the consumers. Clearly, a virtual power plant is focusing on developing strategies to influence and optimise these factors. To accomplish this, many data sets can and should be analysed in order to interpret and create forecasts for energy systems. Time series based analytics are therefore of particular interest for virtual power plants. Classifying the different time series according to generators, consumers or customer types simplifies processes. In this way, scalable solutions for forecasts can be found. However, one has to first find the according clusters efficiently. This paper presents a method for determining clusters of time series. Models are adapted and model-based clustered using ARIMA parameters and an individual quality measure. In this way, the analysis of generic time series can be simplified and additional statements can be made with the help of graphical evaluations. To facilitate large scale virtual power plants, the presented clustering workflow is prepared to be applied on big data capable platforms, e.g. time series stored in Apache Cassandra, analysed through an Apache Spark execution framework. The procedure is shown here using the example of the Day-Ahead prices of the electricity market for 2018.

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

Performance Testing of Coal Fired Power Plants

2007 ◽  
Author(s):  
Shane E. Powers ◽  
William C. Wood
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Performance Test ◽  
Model Development ◽  
Performance Testing ◽  
The United States ◽  
Plant Performance ◽  
Cycle Performance ◽  
Test Program

With the renewed interest in the construction of coal-fired power plants in the United States, there has also been an increased interest in the methodology used to calculate/determine the overall performance of a coal fired power plant. This methodology is detailed in the ASME PTC 46 (1996) Code, which provides an excellent framework for determining the power output and heat rate of coal fired power plants. Unfortunately, the power industry has been slow to adopt this methodology, in part because of the lack of some details in the Code regarding the planning needed to design a performance test program for the determination of coal fired power plant performance. This paper will expand on the ASME PTC 46 (1996) Code by discussing key concepts that need to be addressed when planning an overall plant performance test of a coal fired power plant. The most difficult aspect of calculating coal fired power plant performance is integrating the calculation of boiler performance with the calculation of turbine cycle performance and other balance of plant aspects. If proper planning of the performance test is not performed, the integration of boiler and turbine data will result in a test result that does not accurately reflect the true performance of the overall plant. This planning must start very early in the development of the test program, and be implemented in all stages of the test program design. This paper will address the necessary planning of the test program, including: • Determination of Actual Plant Performance. • Selection of a Test Goal. • Development of the Basic Correction Algorithm. • Designing a Plant Model. • Development of Correction Curves. • Operation of the Power Plant during the Test. All nomenclature in this paper utilizes the ASME PTC 46 definitions for the calculation and correction of plant performance.

Improvement of the Exergoeconomic “Fuel-Impact” Analysis for Acceptance Tests in Power Plants

1999 ◽  
Author(s):  
Alejandro Zaleta-Aguilar ◽  
Armando Gallegos-Muñoz ◽  
Antonio Valero ◽  
Javier Royo
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Field Data ◽  
Impact Analysis ◽  
Performance Test ◽  
Point Of View ◽  
Steam Turbines ◽  
The Real ◽  
Classical Procedure ◽  
Acceptance Tests

Abstract This work builds on the previous work on “Exergoeconomics Fuel-Impact” developed by Torres (1991), Valero et. al. (1994), and compares it with respect to the Performance Test Code (PTC’s) actually applied in power plants (ASME/ANSI PTC-6, 1970). With the objective of proposing procedures for PTC’s in power plant’s based on an exergoeconomics point of view. It was necessary to validate the Fuel-Impact Theories, and improve the conceptual expression, in order to make it more applicable to the real conditions in the plant. By mean of a program using simulation and field data, it was possible to validate and compare the procedures. This work has analyzed an example of a 110 MW Power Plant, in which all the exergetic costs have been determined for the steam cycle, and a fuel-impact analysis has been developed for the steam turbines at the design and off-design conditions. The result of the fuel-impact analysis is compared with respect to a classical procedure related in ASME-PTC-6.

scholarly journals Pilot Low-Cost Concentrating Solar Power Systems Deployment in Sub-Saharan Africa: A Case Study of Implementation Challenges

2020 ◽  
Vol 12 (15) ◽  
pp. 6223
Author(s):  
Emmanuel Wendsongre Ramde ◽  
Eric Tutu Tchao ◽  
Yesuenyeagbe Atsu Kwabla Fiagbe ◽  
Jerry John Kponyo ◽  
Asakipaam Simon Atuah
Keyword(s):  
Electricity Generation ◽  
Power Plants ◽  
Large Scale ◽  
Solar Power ◽  
Low Cost ◽  
Sub Saharan Africa ◽  
Tracking Systems ◽  
Concentrating Solar Power ◽  
Solar Power Plants ◽  
Sub Saharan

Electricity is one of the most crucial resources that drives any given nation’s growth and development. The latest Sustainable Development Goals report indicates Africa still has a high deficit in electricity generation. Concentrating solar power seems to be a potential option to fill the deficit. That is because most of the components of concentrating solar power plants are readily available on the African market at affordable prices, and there are qualified local persons to build the plants. Pilot micro-concentrating solar power plants have been implemented in Sub-Saharan Africa and have shown promising results that could be expanded and leveraged for large-scale electricity generation. An assessment of a pilot concentrating solar power plant in the sub-region noticed one noteworthy obstacle that is the failure of the tracking system to reduce the operating energy cost of running the tracking control system and improve the multifaceted heliostat focusing behavior. This paper highlights the energy situation and the current development in concentrating solar power technology research in Africa. The paper also presents a comprehensive review of the state-of-the-art solar tracking systems for central receiver systems to illustrate the current direction of research regarding the design of low-cost tracking systems in terms of computational complexity, energy consumption, and heliostat alignment accuracy.

Diagnostic Techniques for Improving Power Plant Performance, Reliability and Availability: A Case Study

2006 ◽  
Author(s):  
Komandur S. Sunder Raj
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Performance Monitoring ◽  
Monitoring Program ◽  
Heat Rate ◽  
Diagnostic Techniques ◽  
Lessons Learned ◽  
Plant Performance ◽  
Reliability And Availability

The objectives of an effective power plant performance monitoring program are several-fold. They include: (a) assessing the overall condition of the plant through use of parameters such as output and heat rate (b) monitoring the health of individual components such as the steam generator, turbine-generator, feedwater heaters, moisture separators/reheaters (nuclear), condenser, cooling towers, pumps, etc. (c) using the results of the program to diagnose the causes for deviations in performance (d) quantifying the performance losses (e) taking timely and cost-effective corrective actions (f) using feedback techniques and incorporating lessons learned to institute preventive actions and, (g) optimizing performance. For the plant owner, the ultimate goals are improved plant availability and reliability and reduced cost of generation. The ability to succeed depends upon a number of factors such as cost, commitment, resources, performance monitoring tools, instrumentation, training, etc. Using a case study, this paper discusses diagnostic techniques that might aid power plants in improving their performance, reliability and availability. These techniques include performance parameters, supporting/refuting matrices, logic trees and decision trees for the overall plant as well as for individual components.

Solar Chimney Power Plant Performance for Different Seasons Under Varying Solar Irradiance and Temperature Distribution

2020 ◽  
Vol 143 (6) ◽  
Author(s):  
Ulku Ece Ayli ◽  
Ekin Özgirgin ◽  
Maısarh Tareq
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Ambient Temperature ◽  
Solar Irradiance ◽  
Power Plants ◽  
Low Cost ◽  
Renewable Energy Sources ◽  
Three Dimensional ◽  
Plant Performance ◽  
Solar Chimney

Abstract One of the most promising renewable energy sources is solar energy due to low cost and low harmful emissions, and from the 1980s, one of the most beneficial applications of solar energy is the utilization of solar chimney power plants (SCPP). Recently, with the advancement in computer technology, the use of computational fluid dynamics (CFD) methodology for studying SCPP has become an extensive, robust, and powerful technique. In light of the above, in this study, numerical simulations of an SCPP through three-dimensional axisymmetric modeling is performed. A numerical model is created using CFD software, and the results are verified with an experimental study from the literature. The amount of solar radiation and surrounding weather (ambient temperature) were analyzed, and the effects of the irradiance and air temperature on the output power of the SCPP were studied. Ambient temperature is considered as one of the most important factors that influence collector efficiency in a negative or a positive manner. Solar irradiance is considered to be the most important factor that has an impact on SCPP performance. The investigation includes the study of the relationship between solar insolation and ambient temperatures during the daytime since the difference between the minimum and maximum power values and the performance are very important considering seasonal changes. According to the results, power values are dependent on the amount of solar radiation as well as the ambient temperature, and the importance of selection of location thus climate for an SCPP is found to affect the design of the SCPP.

Modeling and Control of Subcritical Coal-Fired Power Plant Components for Fault Detection

2020 ◽  
Author(s):  
Selorme Agbleze ◽  
Fernando V. Lima ◽  
Natarianto Indrawan ◽  
Rupendranath Panday ◽  
Paolo Pezzini ◽  
...  
Keyword(s):  
Power Plant ◽  
Fault Detection ◽  
Power Plants ◽  
Energy Content ◽  
Leak Detection ◽  
Primary Component ◽  
Plant Performance ◽  
Saturated Steam ◽  
Power Sources

Abstract Due to the increased penetration of renewable power sources into the electric grid, the current number of existing coal-fired power plants shifting from baseload to load-following operations has also increased. This shift creates challenges especially for the power industry as coal-fired power plants were not designed for ramping situations, leading to added stress on major components of these plants. This stress causes the system to degrade over time and eventually develop faults. As boilers are still the primary component that fails and causes forced outages, accurate characterization of faults and fractures of boilers is now becoming increasingly critical to reduce plant downtime and extend the plant life during cycling operations. This work focuses on modeling sections of a subcritical coal-fired power plant and proposes algorithms for fault detection in MATLAB/Simulink. The developed model simulates the process dynamics including steam and feedwater flow regulating valves, drum-boiler, and heat rate on the regulation of pressure, drum level and production of saturated steam. The model also simulates the dynamics of superheaters for increasing the energy content of steam, and a spray section for regulating the temperature of steam upstream of the high-pressure turbine to allow for power output adjustment within a given valve operating range. Furthermore, an extension to a leak detection framework proposed by co-authors in previous work is explored. The new framework includes a modification to the threshold analysis portion of the previous work. The extended framework is then applied to a subcritical coal-fired power plant model for leak detection. In particular, this framework analyzes mismatches or deviations in expected plant dynamics with an identified transfer function model. The mismatch is flagged after it exceeds a threshold. The developed algorithm thus aids in rapid detection of faults to reduce impeded plant performance. The results of this work will support real plant operations by providing an accurate characterization of faults in the operation of coal-fired power plants.

scholarly journals Economic feasibility of developing large scale solar photovoltaic power plants in Spain

2019 ◽  
Vol 122 ◽  
pp. 02004 ◽  
Author(s):  
Javier Menéndez ◽  
Jorge Loredo
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Large Scale ◽  
Economic Feasibility ◽  
Solar Irradiation ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Photovoltaic Energy ◽  
Profitability Analysis ◽  
Photovoltaic Power

In 2017, electricity generation from renewable sources contributed more than one quarter (30.7%) to total EU-28 gross electricity consumption. Wind power is for the first time the most important source, followed closely by hydro power. The growth in electricity from photovoltaic energy has been dramatic, rising from just 3.8 TWh in 2007, reaching a level of 119.5 TWh in 2017. Over this period, the contribution of photovoltaic energy to all electricity generated in the EU-28 from renewable energy sources increased from 0.7% to 12.3%. During this period the investment cost of a photovoltaic power plant has decreased considerably. Fundamentally, the cost of solar panels and inverters has decreased by more than 50%. The solar photovoltaic energy potential depends on two parameters: global solar irradiation and photovoltaic panel efficiency. The average solar irradiation in Spain is 1,600 kWh m-2. This paper analyzes the economic feasibility of developing large scale solar photovoltaic power plants in Spain. Equivalent hours between 800-1,800 h year-1 and output power between 100-400 MW have been considered. The profitability analysis has been carried out considering different prices of the electricity produced in the daily market (50-60 € MWh-1). Net Present Value (NPV) and Internal Rate of Return (IRR) were estimated for all scenarios analyzed. A solar PV power plant with 400 MW of power and 1,800 h year-1, reaches a NPV of 196 M€ and the IRR is 11.01%.

Study on Project of Photovoltaic Power Plant Connecting to the Grid

2013 ◽  
Vol 380-384 ◽  
pp. 3111-3114
Author(s):  
Yi Shi Shu ◽  
Li Li Ma ◽  
Chao Peng
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Large Scale ◽  
Pv System ◽  
Photovoltaic Generation ◽  
Large Capacity ◽  
Photovoltaic Power

Large scale photovoltaic generation is another way to generate electricity.When a large capacity PV system connected to the grid,much impact could be brought to the grid due to its uncertainty. In this paper, there are research and analysis about the technology and characteristics of the photovoltaic power plants connected to the grid, make a strong practical impacts.

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