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Abstract
Continuous and reliable supply of electricity is the boost for the economic development of developing countries like India. With target of maintaining GDP of more than 7.6%, Electric power become the prime movers for manufacturing, agriculture and service sectors. Thermal power generation as on April-October 16 is 684200MU and that of renewable energy source power generation is 53,905 MU. Growth of conventional energy source in last 1 year is only 4.52 % where as growth in Renewable energy source is 28.27%. Greenhouse gas emission from coal fired thermal power plant is a constant threat to climate change and Ecosystem. These result in continuous tightening of emission regulation policy for the thermal power plant. International policy or mitigation like funding from Bank, COP and others are always forcing either to go for cleaner fuel technology or to go for renewable energy source power generation. In the last decade lot of improvement has been done to utilize abundant storage and cheap availability of coal for electricity generations. In this paper new emission regulation, adopting clean coal technologies, cyclic load operation, base load operation, creep life consumption, fatigue life consumption and etc. are explained properly. Trends for higher efficiency and less emission technologies like adopting super critical, ultra supercritical boiler over sub critical are already started. Advance Ultra supercritical boilers are also under final research stage. On the other hand renewable energy like solar power got huge boost in progress due to government incentives like (i) benefit on the basis of net metering laws that allows the end user endd users to sell electricity at retail prices again in to the grid, (ii) even subsidies given to the customer to decrease the overall cost after complete installation, (iii) loans are given to other companies at very low rate and also tax incentives. The topic will also cover both Technical like grid integration of renewable power with the conventional power, mechanical stress cycle of plant equipments due to frequent under scheduling, financial burden due to operating at part load operation, generating more efficient and cheap power and etc. Lastly the most innovative part of this paper is the forecasting mathematical model has been explained. The model will give preliminary ideas and help in forecasting some of the major parameters that generally closely interlinked with the cyclic operation or base load operation due to high penetration of renewable energy in to the grid.  So after addition of more renewable power to grid, the future steps for thermal power plants will become more exigent unless there will be adaptation of new clean coal technologies.
Keywords: (Power, Emission, cyclic operation, renewable energy, Forecasting,)

Introduction
Electricity becomes the prime movers for boosting the economic growth in India. As on date 31st November 2016, total installation capacity of Indian Power generation has increased up to 308834.28 MW, out of which 45916 MW is renewable and 4313MW [1] is hydro. The overall growth in Indian power generation from the past decades shows tremendously high. From the year 2007 to 2015 increase percentage of conventional power generation is dominating over the Renewable power generation growth, but after the year 2015 the scenario becomes reverse.  After the mission for 175GW of renewable power generation it is now becomes challenges for the thermal power plant in India. Conventional power plant will face the considerable impact of an increased penetration of renewable power generation in to the grid. This will directly impact on the revenue for the owners of conventional power plants.  For thermal power plant the loss factors that to be consider as a whole are as electricity cost, fuel type, nameplate capacity, operating condition, geographic location, load cycling cost, start up cost, total O&M cost, fuel cost, breakdown cost and etc.
Thermal power plants are the biggest contributor of emission in India. Nearly 70% of greenhouse gas and others pollutant like SOx, NOx, and Hg are comes from thermal power plant. There is a continuous pressure from international bankers, policy makers and other recognized organisation to limit the greenhouse gas and emissions from thermal power plant. This result in implementation of new emission rules after 1st January 2017, by Ministry of environment Forestry and climate change (MoEF&CC). This rule brings more financial burden to the plants owners especially for those plants whose plant load factors remains below 50%. 
This paper also discusses about technical challenges consists of grid integration, specific emissions, blackout probabilistic, that directly and indirectly impacting on load cycling, load ramp up, load ramp down, creep and fatigue life of the Thermal power plants. When a generator is shutdown and restarted its combustion, steam and water system are subjected to significant temperature transients, which definitely initiate creep-fatigue, fatigue, and other life consumption mechanism. So, the creep resistance steels are not able to withstand, and thus it leads to degradation and acceleration of damage rate. Lastly the most important and innovative mathematical model has been explained that will able to forecast the creep life consumption, fatigue life consumption, base load operation, light up oil consumption after high penetration of renewable power in to the grid. 
Technical challenges and Analysis
Conventional Power generation plant will face the enormous impact of an improved penetration of renewable energy technology in to the grid. For thermal power plant the hammering elements that to be recollect as a whole are as power value, type of fuel, nameplate capacity, operation condition, geographic area, load cycling cost, start up and shut down cost, overall O&M cost, fuel cost, breakdown fee and etc. It may be forecast that on elevated penetration of renewable power generation in 2022 will set off certain percentage increase in the starts-up of thermal Power plants and increase in load ramp up. The energy gadget will even face the challenge from the boom in renewable electricity era, for example, because of the penetration of renewable energy in to grid, the load-demand shifted far from the demand centers, then there is an expanded need for excessive voltage electricity transmission, furthermore the accessibility of power on windy and sunny days will motive the power charge drops. Additional challenges and opportunities arise from the fact that the most manufacturing or production at some stage in hours may not always meet by using renewable energy. So there will be an increased in cycling operation of thermal power generation to balance the power grid. To avoid immoderate curtailment of thermal power generation [1] in power system with excessive penetration of renewable power, greater ramping capabilities and a larger range of operations will need to offer by thermal energy plant.

Damage mechanism of thermal power plants
While renewable energy is available then it's far given dispatch priority, forcing thermal power generation to off precedence. Consequently many base load plants will be forced to function cycling. This offers upward thrust too many extreme challenge increased aging, shortened lifespan and massive hike in operational cost that can result [2, 3] from off-designed operation. Whilst the load of providing dynamic generation, dispatchable, to assist variable renewable energy may shift to such stage that the large generating plant which are designed for a lifespan of has designed life span of 25 years (or 40 years) may have to run either in base load or cyclic operation for the rest of life. So renewable electricity integration must overlook the effect of high stage of cyclic duty on thermal power plant.

All working regimes results in burning up of service life through combination impact of creep, fatigue, corrosion, erosion [4] and different damage mechanism which amassed over the years. Generating plant proposed for base load regime perform most efficiently in steady state circumstance in which load, and consequently temperature, strain, pressure and fluid flow are maintain for a long time frame. Such operation gives rise to [5, 6] creep damage. Power plant steels can describe as a deformation which occurs when the material is subjected to constant pressure at [7] excessive temperature. Creep is dominant damaged mechanism in the additives of excessive temperature for all power plants running in base load [8], and become formerly life limiter factors. Materials and technology are only decided by the power plant designer after complete analysis on their capacity to face up to high temperature creep conditions over [9] extended period length.

The impact of other damage mechanism increases, while plant designed to operate in creep situations are subjected to function repeated start/stop cycling. When a generator is shutdown and restarted its combustion, steam and water system are subjected to momentous temperature transients that can initiate fatigue, creep-fatigue and different life consuming mechanism which creep resistance steels are less capable of resist, leading to improved damage [10] and degradation rates for components and system.  At the same time as erosion and corrosion can be extended by way of Cycling, its creep and fatigue also have been diagnosed as the important parameters affecting the life consumption rate for the base load units and hence their performance need to analyze more.  To be able to achieve greater durability, increase in maintenance cost different non preferred renovation cost and change needed to be undertaken, entailing significant expenditure above that over recurring operation and renovation. 

Thermal fatigue [11] damage is the most common problem resulting from cycling or base load operation. This may be appearing both as cracking or entire mechanical failure. Immoderate thermal gradients in steam metal and temperature accomplice with rapid change of conditions seen for the duration of start-up, load ramp-up and shut down result in cracking. In general the boiler superheater headers, the temperature changes purpose joint deformations. Other damages are the bursting of pipe, valve damages, coating failure, quenching damages [12] because of condensate formation. Increase in the failure rate is key evidence due to increase in equivalent compelled outage Rate (EFOR) [13] and reduction in unit availability. So creep and fatigue act together synergistically leading to increase in aging and premature factor breakdown.
Effect on cost of electricity production 
The every year station heat rate will directly get impact from the penetration of more renewable energy era in to the grid. Since the rate of huge fuel is relies upon at the time and area of the fuel resources and the fuel rate best constitute 50 � 80% of a thermal electricity plant�s [14] overall O&M value. Therefore the income margin will substantially get affected for the thermal power plant in India. After all the overall cost of electricity production is a characteristic of primary fuel kind and nameplate potential.
Cost of cycling
Start, stop process, minimal load operation and load following ramps, which are normally referred to as plant cycling result in thermal stresses in various a part of thermal power plant. Throughout the years these thermal stresses can cause material fatigue and damage. Therefore cycling of thermal power plant has unfavorable effect on the economic performance and lifetime of the plant. Especially for each thermal electricity unit, operational constraints, namely load ramping and start up cost are function of fuel type and nameplate capacity. Another situation like for idling plant , the price of electricity production is multiplied with tabulated cost thing that account for the additional fuel consumption and the cumulative aging of element life time due to the required form of starts. Usually ramp is defined as a 50% increase in load inside six hours. So for the devices in operation at the taken into consideration as, component degradation due to ramping might be accounted. Ramping to one-of-a-kind power level is results in a ramping rate and the value of ramping will increase linearly with the significance of the ramp. So after penetration of 175GW to the grid, there will be increase in ramping percent, emphasizing the importance of each OEMs and utilities to account for power plant cycling in destiny markets. 
With the growth in renewable strength era, the plant load factors gets decreased and so utilities can't depend on the elevated load factors to catch up on the economic setback to be able to be incurred from accelerated cycling operation. it could also be estimate that with the increase in Renewable electricity penetration, the transmission line loading decreases however fashionable deviations of line loading can be extensively increases. 
Blackout probabilistic
Renewable power integration and deregulation imply that the electric grid will function close to it limits inside the future and that of the variety of integrations flows will growth. As the combination of power flow between renewable and traditional technology from supply to sink will increase, the blackout probabilistic like cascading failure will also increase which is consider to be most common failure and is called cascading outage. A large sort of mechanism is concerned inside the cascading outages like common mode failure and hidden failure, excessive static loads after power flow redistribution that could result in additional thermal failure.
Base load cycling operation
Increase in Renewable energy technology, it'll result in suboptimal operation of base load generating units in India. In spite of the reality that these thermal generation plant are not designed to operate in a bendy manner, the deregulation of the electricity  ought to result in these base load unit being close down or operated at part load levels frequently. This cycling operation could have arduous effect on the component of those units and potentially increase in outages and significant cost. The following elements are the some of the reason for base load cycling operations of the thermal power plant: 1. Renewable power a variable power supply and fluctuations in output need to be offset to maintain the supply/demand for balance, consequently ensuring in extra demand in operation flexibility [14] from the thermal power plant in to cycling. 2. These units should also deliver additional reserve to preserve system reliability ought to a sudden drop in renewable power generation. 3. The day hourly prediction of renewable power generation by and large because of wind can vary by 10% to 15% [16] of the total capacity, that may bring about thermal gadgets over or below committed. In addition greater if renewable is given self-despatch, in order that forecast output is not included inside the day beforehand schedule then this could lead to elevated transmission constraints  thus intensify plant cycling. 
As those units are designed with minimum operation flexibility, cycling those units will effects in elevated deteriotion of unit component through various degeneration mechanisms along with fatigue erosion, corrosion, etc, leading to more frequent compelled outage and lack of earnings. The interruption to operation as a result of cycling disrupts the plant chemistry and consequences in higher amount of oxygen and different foreign particles leading  to corrosion and fouling issues. Excessive cycling of base load units ought to potentially leave them completely out of operation prior to their predicted lifetimes. Environmental penalties [17] will increase because of increase in fuel uses. Also cycling related damage may not be without delay obvious and it may take seven years to get prominent within the failure charge to come to be apparent after switching from [18] base load to cycling. 
Effect on intermediate pressure regulating valve due to cyclic operation
Failure of turbine valves frequently came about in many power plants because of severe temperature and excessive pressure operating environment resulting from cycling operation. Research were completed in Finite detail version (FEM), thinking about the factors like cold-start up, hot start-up, warm start-up, shut-down, load ramp-up , base load operation and emergency shutdown to discover the maximum stress range seems near the stiffening ribs inside the valve frame, circumferential thermal stress concentration area. It has also been concluded that the damage in the course of turbine emergencies shutdown contributes the main element to the damage fatigue functionality which described because the quantity of cycle to crack- initiation inside the valve because of cycle working situations. Because of cyclic operation continually advocate that temporary thermal stress analysis and fatigue existence estimation of the valve body are necessary. The valve frame additionally undergoes varying steam pressure and temperature in the course of load ramp up and ramp down, and it'll also undergo the impact stress by means of the valve spindle throughout the valve open or close operation. Moreover fatigue brought about by means of cyclic thermal strain cause the [19] valve failure as a result FEM has analyzed that whole turbine operation from start up, load ramp up, load ramp down to shut down, the circumferential transient thermal pressure undergoes both compression strain and maximum anxiety stress. Thus the amplitude of cyclic circumferential stress is the main factor that induces fatigue and crack.
Effect on emission from cycling operation of thermal power plants

After penetrating 175GW of renewable power by 2022 in India, there may be a chance that the cyclic emission of thermal electricity plant will increase.  research have shown, after the existence cycle evaluation a number of the thermal electricity power plant in European international locations during their complete life cycle, that there may be high capability to growth the specific emissions [20] level because of variable output power generation from the renewable electricity assets. Those variable renewable power generations will result in higher greenhouse gas emission because of greater fuel volume being used and additionally, air pollutants control device that mitigate different emissions, inclusive of NOx may not operate optimally [21], while the generator output power is changing, similarly increases the specific emissions. Emission in keeping with unit electricity generated from thermal strength plant for cyclic operation, because of variable renewable electricity generated want to be calculate.
In this paper one scenario of such base load or cyclic operation has been taken. The 660MW supercritical units of reliance power ltd, the emission parameter taken from full load to base load cyclic operation. The specific emission (i.e. emission per unit power generated) is being calculated.  It has been observe from the below table 1. that as the load decreases from the full load, the CO2 increases and the emission per unit generation is also increases. Thus the Life cycle assessment of future thermal power plant in India will able to investigate emission due to cycling, how relevant were cycling impact compared to the overall emissions, which power plant type most effected, and how different power plant mixes influences overall emission due to cycling.
Table: 1. Specific emission at different load of an supercritical unit.Load (MW)660Specific emission@660 (mgNm3/MW)425Specific emission@425 (mgNm3/MW)270Specific emission@270 (mgNm3/MW)NOx (mg/Nm3)3660.558752.0510043.71SOx (mg/Nm3)9461.437321.726112.26Dust(mg/Nm3)290.04280.06280.103CO2 (gm/kwh)7928891106 Forecasting analysis Model of different parameter due to cycling operation
After penetrating 175GW of variable Renewable Energy power generation by 2022 in India, the scenario could by more complex on thermal power plants operation that resulting burdening total fixed and variable cost.  So analysing and forecasting the future burdening scenario is done in this model. In this paper, the data of one of the 660 MW supercritical units has been taken. As per present trends of cycling, ramp-up and ramp down operation some of the vertical or probabilistic data also taken.
For plotting in X and Y coordinate graph are creep life consumption- measured in cumulative online hours and fatigue life consumption measured in cumulative starts vs. Age in calendar yr. At interval of one years of online hour�s operation the cumulative values are plotted on the Graph. With this the anticipated quantity of begin at interval of one year are also then plotted. 
Mathematical model Discussion: The model used the least square regression method principal for forecasting as well as for finding out the particular year desired result. The least square is used where many more experimental data are available than the parameters. This process is widely used and is often believed to be the right one to use. Experimental data is usually scattered and is a good example for inexact data. The principle of least squares is one of the popular methods for finding a curve or straight line fitting a (x1, y1),...... (Xn, yn) given data. Say, be n observations from an experiment. The desired equation is to fit in straight lines for i=1,2,3...n can be written as
 yi = axi + b					(1)
Finding for n number of readings and residual value ei  
 ei = yi � (axi + b),    i=1,2,3...n			(2)
Now considering the sum of square ei is E = �i=1(ei2)
= �i=1[yi - (axi + b)]2 				(3)
To find the value of constant  a  and  b  the above equation-3 to be minimum is given by 
nE/na = nE/nb = 0 				(4)
After differentiating above equation-4, two simultaneous equation will get.
a�i=1 (xi)2 + b �i=1(xi) = �i=1(xi.yi)			(5) a�i=1 (xi) + n.b = �i=1(yi)				(6)
Solving the equation 5 and 6, straight line equation y=ax+b.
For example 1: In X and Y axis, shown in figure 1, creep life consumption- measured in cumulative online hours and fatigue life consumption measured in cumulative starts vs. Age in calendar year are taken. Below Table 2 showing the value.
Table: 2. online operation and number of start vs.  Calendar year
X(Age)12345y1(online hour operation)744014400230402784036600 y2(start/year)2018151710Experimental data may not be always linear. One may be interested in fitting either a curve in the form of 
y = axb						(7)
This form can be linearized by taking logarithms on both side and compared with the straight line equation               Y = A + bX.
Log10y = log10a + b.log10x				(8)
Y = Log10y, A = log10a, X = b.log10x
After solving staright line equation and then linearized to form normal equations, the power trend line for the relationship between the unit age and the creep life consumption or cumulative online hours operation, which has a form:
Straight line equation: Y = 0.9668*X + 3.875	(9)
Normal equation:	        y = 7447x24/25		(10)
x is age in calendar year, y is creep life consumption in online hours.Similarly the relationship between age in calendar year and fatigue life consumption, measure in cumulative starts can be written by solving both straight line and normal equation as follows.
Straight line equation: Y = 0.8721*X + 1.308 	(11)
Normal equation:	         y=20x0.87			(12) Both curve showing strong positive correlation with a coefficient of determination R2 are 0.9 each.
In this model the forecasting for creep life consumption in term of online hour operation and the machine fatigue life consumption, for any particular can be easily calculated by differentiating both the normal equations 10 & 12. Let the year taken be as 12th  year. 
Online hours of operation for the year 12 (x=12)
y = 7447*(24/25)x-1/25 = 6475 online hours.

Number of days: 6475/(24)= 270 days of operation. 
Fatigue life consumption in term of number of start, for the 12th year i.e. x = 12, can be calculated by differentiating the equation 12.

y = 20*(0.87)*x(-0.13) = 12.60 round off to 13 starts. 	

     EMBED MSGraph.Chart.8 \s 
Fig :1. Online operation and number of start vs.  Calendar year
For example 2: Another two very important parameters shown in figure 2, that can be forecast with the help of both straight line and normal equations. Those two parameters that are highly depend on penetration of more renewable powers in to the grid are back down and HSD or LDO light up oil consumption. Back down or running the unit at base load that generally followed as per grid management. Oil consumption is due to two reasons; one is due to cyclic operation of thermal power plant and another is due to oil support that generally used to provide when the unit is run below technical minimum loads. Both these parameters have been analysis with the help of least square regression equations. Minimum 5 reading for consecutive 5 years are taken. The final normal equation of these example data will able to give forecasting data of any particular year.
Table:3. Curtailment in MU and oil consumption in KL vs calendar year
X(Age)12345y1(Back down in MU)410450510554590 y2(Oil Consumption)33243452312028602590 EMBED MSGraph.Chart.8 \s 
Fig:2. Curtailment in MU and oil consumption in KL vs calendar year
As per the values from table:3, the above scattered graph has been drawn. In X and Y axis, Age in calendar year taken vs.  Cumulative back down in million units(MU) due to high penetration of renewable power and cumulative oil consumption due to cyclic operation or oil support due to running the units below technical minimum load are taken. The curve is drawn on the principal of least square both linear and non linear regression equations. However the simplest narrative description of the rate of back down and oil consumption per year are more viable in this least square non linear normal equation y = axb, and can be more easily  linearized   with the help of logarithm principle.
Solving for cumulative back down in MU with the help of equation 1 and 7 is   y = 1.126x + 2.605		(13)
Thus linearizing the above straight line equation by taking equation 8, the result is  y = 402.71x1.126		(14)
Again solving for cumulative oil consumption, after implementing same steps, the resulted equation can be written as      y = 0.9530x + 3.532			(15)
Similarly after lnearizing the above equation, the resulted equation is    y = 3404x0.95				(16)
Equation 14 and 16 are the final equation for cumulative back down in MU and cumulative oil consumption. With these above equation the forecasting model analysis can be done and able to find out the desired value for any particular year. To find out the forecasting values for the say year no. 9 i.e. x = 9.
So, for the 9th year Back down in MU is:
y = 402.71*1.126*x.126 = 598.05 MU.
Again to get the oil consumption for the 9th year can be derived from the equation 16 
y = 3404*0.95*x(-0.05) = 3404*0.95*9(-0.05) = 2897.67 KL.
In these model four important parameters which are closely affected by the cyclic operation of unit which can be of course is the impact of high penetration of renewable energy strength technology has been highlighted. the ones parameters are as 1. Creep lifestyles consumption suggests as on line hours of operation. 2. Fatigue life consumption as variety of begins/stop operation of units. 3. Curtailment from the grid or the base load operation. 4. Oil consumption due to cyclic operation of unit after high penetration of renewable electricity power technology in to the grid. Therefore this model will offer preliminary ideas and one step beforehand for forecasting facts with a lot easier calculations
Conclusion:
Technical challenges have been highlighted properly taking most possible factors, after 175GW grid integration of Renewable power generation. Power system, transmission line and power plant will face lots of challenges due to high penetration of renewable power generation in to the grid. Damage mechanism of thermal power plant, discussing about the creep life consumption, fatigue life consumption, corrosion, erosion, specific emission are all highlighted. Once the unit operates at name plate load, the operation and maintenance cost is nominal or as per design but once the plant goes under base load or cyclic operation, all the problems arises thus operation and Maintenance cost also increased. Cost of electricity production will definitely goes high with very marginal or not profit. Blackout probabilistic also increases in the power system. As per rule the more the connection with the renewable power generation, the more is the blackout probabilistic. Under cyclic or base load operation, crack on intermediate pressure regulating valve is also observed. Emission is also shows high degradation at base load or cyclic operation because the emission control technologies will shows poor performance while load ramping up, down or base load operation. 
Lastly the innovative part of the paper has been highlighted with the help of mathematical model.  With the help of least square linear and non linear regression equation, it can able to forecast some of the important parameters those are highly affected by the cyclic operation of the grid. Parameters like 1. Creep life consumption indicates as online hours of operation. 2. Fatigue life consumption as number of starts/stop operation of units. 3. Back down from the grid or the base load operation. 4. Oil consumption are taken and analysis to get the forecasting value. This model is the basic and simple calculation that can support the any details complex calculation. 
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