Ppt performance evaluation of solar thermal power plants

Performance Evaluation of Solar Thermal Power Plant

Guided by: Presented by:

Dr. R. P. Saini Md. Zafar Alam

Associate Professor M.Tech II Year

AHEC ,IIT Roorkee Enroll. no: 13512017

CONTENTS• Introduction

• Needs of renewable energy

• Resources of renewable energy

• Classification of solar power generation

• Solar thermal power plant

• Components of Solar Thermal Power Plant

• Types of Solar Thermal Power Plant

• Performance Evaluation Of Solar Thermal Power Plant

• Factors Affecting Solar Thermal Power Plant

• Critical Parameters of CSP

• Conclusion

• Scope of work

• References

INTRODUCTION

Energy:

•Energy is the basic requirement for economic development.

•There has been an enormous increase in the global demand for

energy in recent years as a result of industrial development and

population growth.

• Since the early 2000s the demand for energy was from liquid fuels.

Limits on the rate of fuel production has created such a bottleneck

leading to the current energy crisis.

•Today, there is a huge energy crisis in India as power generation

does not meet the power requirement.

Per capita energy consumption scenario [1]

Per capita consumption of energy in India is one of the lowest in the world

.Needs of Renewable Energy• May fulfill the gap of energy demand and supply.

• Environment friendly.

• Reduce the dependability on fossil fuels.

• Better energy resources for isolated areas.

• Fossil fuels are finite resources.

• Fossil fuel contribute to climate change.

Sources of Renewable Energy

Classification of solar power generation

Solar Photovoltaic

Photovoltaic (PV) is a method of generating electrical power by converting solar radiation  into  direct current electricity using semiconductors that exhibit the photovoltaic effect.

Solar Photovoltaic Electricity Generation

SOLAR THERMAL

• In solar thermal energy from the sun is collected at collector and converted it into heat.

This heat can be used in -

• conventional power plant

• water heating

• air heating

• hydrogen production

Solar Thermal Power Plant• In solar thermal plant thermal energy obtained from

sun radiation is converted into electricity by using conventional power cycle.

Solar Thermal Power Plant[3]

Solar Field

PowerBlock

Components of Solar Thermal Power Plant

• Reflector

• Absorber

• Tracking and Controlling

• Heat Transfer Medium

• Thermal Storage

• Power Block

Types of Solar Thermal Collectors

Fresnel Collector

Central receiver Dish/ Stirling system

Parabolic trough plant

Factors Affecting Performance of Solar Thermal Power Plant

• Variations in solar radiation

• Characteristics of solar collectors

• Geometrical factors such as shadows, length of collector, orientation etc

• Losses due to convection, conduction and radiation

• Losses in heat exchanger

• Change of phase of circulating fluid in power block

• Velocity of cloud

• Dirt on concentrator

• Velocity of wind

Critical Parameters of Solar Thermal Power Plant

• Mass flow rate of fluid• Inlet temperature of working fluid• Geometry of concentrator• Optical parameters• Irradiation

Uncertain Parameters of Solar Thermal PlantVelocity of windCloud velocityIrradiationWeather condition

Methods used to evaluate performance of CSP Plant

1. Analytical Approach2. Software Analysis3. Laboratory Method

Analytical Approach

• Optical efficiency

• Collector Efficiency

• Efficiency of Power block

Software Approach

• The models and codes can be grouped according to a “modeling pyramid” which describes a natural hierarchy for performance of solar thermal power plant.

Illustration of the modeling pyramid[6]

Input Parameters and There Measurement

Parameter Measuring Technique/Tool

Geometry of the system Laser beam

Solar radiation Solarimeter

Mass flow rate Flow meter

Temperature Thermometer

Enthalpy Using steam table

Heat transfer coefficient Known

Reflectivity, absorptivity and Transmissivity of the system

Material property

Methods:

1. Deterministic method 2. Probabilistic method Deterministic method In deterministic evaluations of the system or component

performance yield a single value for the simulated output. Input parameters are typically entered as specific values rather than distributions of values that honor the inherent uncertainty in many of the system features and processes. As a result, the confidence of the result and uncertainty associated with the results are not reported.

Software Used To Address Major Components of CSP Technology

Component Software/Code

Solar Collectors

ASAP, CIRCE, SOLTRACE, FLUENT

Heat Transfer Fluid (HTF) Transport, Exchange, and Storage

FLUENT, SAM

Stress Analysis Codes CosmosWorks, ANSYS

Power Cycle GATECYCLE, STEAMPRO

Total System Performance DELSOL, SAM

Probabilistic method

• It quantify the impact of system uncertainties on the simulated performance metrics.

• The confidence level of the simulated metric being above or below a particular value or range can be readily assessed and presented using these probabilistic methods.

• sensitivity analyses can be used with probabilistic analyses to determine the most important components that impact the simulated performance.

• Code used SAM, SOLERGY

Comparison Between Deterministic and Probabilistic Method

• Graph below shows a hypothetical plot of the levelized energy cost (LEC) for a solar thermal power plant calculated using both probabilistic and deterministic methods.

• In both methods, the LEC is calculated using the equation-

• In the probabilistic model, each of the four variables in equation is treated as an uncertain parameter. Each variable is represented by a uniform distribution of values.

Levelized Energy Cost $/kWh

Source: Clifford K. Ho et al.

S. No. Author(s) Study(s) Result(s)

1Joel Anderson et al

used CasADi to evaluate the performance

it is more user interactivity, provide Symbolic/numeric algorithms and push the limit on speed & size

2 L.J. Yebra

analysis of Object Oriented Modelling of DISS Solar Thermal Power Plant

developed a dynamic models for use in simulation and control of this type of solar power plant

3 Juany M. Valenzuela

discussed performance of a 50 MW concentrating solar power plant

Used GateCycle and Set macro software. These types of macros assign a mathematical expression to a user-defined variable. In this case a variable under the name of “steam cycle efficiency” was created

4Naum

Fraidenraich et al

performed analytical modeling of direct steam generation solar power plants

A physically transparent understanding is provided for heat transfer within the collectors, heat loss to ambient, fluid flow and steam cycle efficiency and concluded that Model predictions agree satisfactorily with results from the INDITEP DSG project

Literature review

5J. Marti

Herrero et al

aim is to form a mathematical dynamical model to evaluate the performance of a solar chimney

Used concept of thermal inertia applied to the mediterranean climates and found that it provide satisfactory results that do not contradict the experimental data.

6

P. Fernánde

z et al

Perform analysis of a gas turbine driven CSP plant.

used thermo-fluid dynamic modeling with Monte Carlo Ray Tracing method. The CFD solver and the Monte Carlo method have been coupled together via User-Defined Functions (UDFs) and iterate alternatively until convergence. Result obtained from this is close to experimental value.

7

C. Gertig et al

a new software SoFiA for the Central Receiver Systems is proposed. SoFiA approaches difficulties in a staged way with different quality levels.high,medium and low quality

concluded that HQ Models is time consuming and detailed information must be available. An interface with a model based on Finite Element Method (FEM) will be established to import and export solar flux distributions on complex receiver geometries and then evaluate the temperature distributions and material stresses.

8Clifford Ho et al.

probabilistic modeling of concentrating solar power plants

Found that it is complex but gives best result

CONCLUSION

Based on literature review it is concluded that – Performance of a solar thermal power plant is affected by

various uncertain and sensitive parameters. performance of csp plant is calculated by different methods In deterministic method uncertainty and sensitivity related to

solar thermal power plant is not cosider and provide approximate result that is different from actual value.

Probabilistic method consider all the uncertainty and sensitive parameters related to solar thermal plant hence provide result close to actual.

Scope of future work

• To identify sensitive and uncertain parameter affecting the performance of solar thermal power plant and there distribution.

• Improvement in probabilistic method of performance evaluation.

• Automatic start-up and shutdowns of the plants is one of the main objectives so that plants operate in the most autonomous way.

References

1. ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=62162972. V.Shivareddy ,Renewable and Sustainable Energy Reviews 27 (2013) 258–2733. www.conversionconversion.com4 http://www.renewables-made-in-germany.com/en/renewables-made-in-germany-5. Adel Kahlil, a Thesis Submitted to the Faculty of Engineering at Cairo University.6. Clifford K. Ho,”Software and Codes for Analysis of Concentrating Solar Power

Technologies”, SAND2008-80537. Joel Andersson and Moritz Diehl, “optical control of solar thermal power

plant”, Toulouse, 21 September 20118. L.J. Yebra, M. Berenguel, E. Zarza and S. Dormido, “ Object Oriented

Modelling of DISS Solar Thermal Power Plant”, PSA-CIEMAT Modelica 2006

9. Juany M. Valenzuela,” performance of a 50 Mw concentrating solar power plant politecnico di bari mechanical engineering final thesis, academic year 2010-2011

10. J. Martı-Herrero and M.R. Heras-Celemin,“Dynamic physical model for a solar chimney”, Solar Energy 81 (2007) 614–622

Continued

11. P. Fernández and F. Miller’ “Assessment of the overall efficiency of gas turbine- driven CSP plants using small particle solar receivers”, Energy Procedia 49 ( 2014 ) 334 – 343

12. Ho Clifford, Khalsa Siri S., and Kolb Gregory J., “Methods for probabilistic modeling of concentrating solar power plants”,US Department of Energy Publications. Paper 115

Thank you…