Enhancing the Energy Efficiency of a Supercritical Thermal Power Plant Through Improved Plant Load Factor, and Optimized Performance of Auxiliary Equipment

Thermal power plants are the measured sources of energy for the production of electrical power, and they generate different pollutants in the environment. Ecological effluence may be lessened by either minimizing the energy consumption or by generating high-efficient energy. In power plants some part of the energy being consumed by different auxiliary types of equipment. The auxiliary power is different for diverse plant sizes from 20 MW to 660 MW plants, varied between 13-4.75%. The Estimated auxiliary power used in 660 MW thermal power plants is 31.3 MW/hour; this generates CO₂ emission by 751.2 t/d. Thermal power plant’s obtainability fundamentally depends on the availability of fuel, water facility, auxiliary systems, ash disposable stations, load dispatching centers and operation and maintenance reliability. There are so many reasons that auxiliary power consumption in India is higher than the other developed countries. Those are excessive feedwater flow, excessive steam flow, ineffective drives, deficiency of maintenance of apparatus, poor coal quality, internal leakage of equipment, lack of technology up-gradation, oversizing of equipment, and usage of unproductive control systems. Reduction in the auxiliary power by 0.5% may add 28.38 MU of additional power into the grid and 26,963 t/y CO₂ emissions could be reduced.

Supercritical once through units gives the maximum plant efficiency due to less losses from the boiler like unburnt carbon losses, dry flue gas losses, less moisture loss in combustion air and radiation losses and generates fewer pollutants than other subcritical and critical technology-based plants. Figure 1 shows the schematic of the 660 MW plant. In many countries, the vastly fluctuating grid frequency due to earthquake, physical attack, cyber attack, operations error, tsunamis, regional weather, ice storms, floods, space weather and other electromagnetic threats, hurricanes or tropical cyclones, wildfire, drought etc. This compels power units with superior part-load efficiency to realize greater economic power generation. Supercritical once through drum-less units are very useful for part load generation. Figure 2 shows the detailed process diagram and equipment.

1.1 Auxiliary power improvement

Bhatt and Mandi's [1] study indicated that the auxiliary power increases as gross energy generation (GEG) increase at full load conditions. They have identified the influencing parameters such as coal quality, excess steam flow, internal leakages, and inefficient drivers. Harley et al. [2] had studied bowl mills in pulverized coal boilers, at higher fineness (below 75 microns) power consumption of the mill is more and some carbon molecules escape from the furnace to increase carbon unburnt in fly ash. At low fineness (above 75 microns) power consumption of the mill is less than the designed values by adjusting rollers. Bhowmick and Bera [3] had studied the Induced draft performance, they had proved that Induced draft fan performance reduced due to over-design and older design (old electrostatic precipitator). Mandi et al. [4] studied the energy efficiency methods of boiler feed water pump in 210 MW thermal power plant. Their study indicated that the auxiliary power is reduced when the pump operated at 100% plant load factor. Also, the absence of re-circulation reduced the auxiliary power of the boiler feed water pump. Kumar and Rao [5] had studied the auxiliary power consumption of the total plant. Around 8% of energy generation from the plant was used to run the auxiliary equipment, and 30% for the boiler feed pump. Saha and Chatterjee [6] had compared the Indian auxiliary power consumption to other countries. They had concluded that Indian power generation units auxiliary power depletion are upper-sided due to low plant load factor, the higher ash content in coal, more steam flow, and feedwater flow consumption, lack of knowledge in the operation of utilities, design defects, etc. Adate and Awale [7] had studied boiler feed pump auxiliary power consumption and various factors affecting the auxiliary power consumption of boiler feed pump. They had concluded that the auxiliary power consumption of the feed pump could be decreased by enhancing the plant load factors. Raval and Patel [8] had studied different auxiliary power consumption and different improvement methods. They had studied in detail pumps and compressors, as these two are main auxiliaries that consume maximum power from the generation. Tsang [9] had experimented on impeller trimming (reduce the size of the impeller) of centrifugal pump. He had concluded that more trimming of impeller caused misalignment of impeller and casing. Chikkatur and Sagar [10] had done different studies about ash percentages in different coal, mill performance, and pollution generation. They concluded that 50% ash content in coal mill could increase power by 7.2% than the designed power.

1.2 Plant load factor improvement

Mandi and Yaragatti [11] had studied energy efficiency on 210 MW coal-fired power plants and concluded that the operation of the plant with improved PLF reduces the specific auxiliary power. Mandi and Yaragatti [12] had done energy-saving procedures in a 210 MW coal-fired power plant and concluded that the operation of the plant at enhanced PLF condensed the auxiliary power, net auxiliary power, and CO₂ emission. CEA [13] had experimented on power plants with different plant load factors. Results indicated that by using supercritical and ultra-supercritical power plants, the plant load factor was improved and simultaneously specific auxiliary power was also decreased. Gomez [14] had studied rotary air preheater in a 210 MW coal-fired thermal power plant. He had done a detailed study in primary and secondary air heat extraction from flue gas. He had concluded that due to high pressure developed by PA and SA than flue gas, there was air leakage through APH that increased the gas flow and loading of ID fan. Sathyanathan and Mohammad [15] had studied the carbon percentage in both fly ash and bottom ash. They had found that fly ash combustibles depend on proximate analysis and GCV of coal, whereas bottom ash combustibles depend on coal particle size (50 mesh particles).

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Figure 1. Line diagram of 660 MW Supercritical thermal power plant [1]

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Figure 2. A 660 MW supercritical power plant schematic representation [16]

1.3 Optimization of pollution levels

Krol and Oclon [17] had studied the performance improvement prices and CO₂ emission prices. They concluded that CO₂ emission and fuel cost had a strong influence when coal handling plants connect with condensing turbines at low pressure. Javadi et al. [18] experimented on a 500 MW combined cycle power plant for the optimization of CO₂ emission, system exergy efficiency, and energy cost to reduce the heat rate. Manzolinia et al. [19] had worked in the STEPWISE H2020 project and the SEWGS technology integrated with Iron and steel plant to know CO₂ emission levels. They concluded that the SEWGS technology has enhanced steam consumption that increases energy. Kumar et al. [20] had studied coal thermal power plants in terms of emission taxation and used linear programming-based data envelopment analysis (DEA) to estimate boiler efficiency. Chen [21] had examined the changes in productivity from the regulations of the environment to control the CO₂ emission in thermal power plants. They concluded that measuring productivity advancement by shadow pricing is more than the actual trading price of CO_2. Liu et al. [22] had studied different environmental and pollutions issues from thermal power plants in China, they have concluded that in China thermal power plants releasing greater emissions than other sectors. Lysko et al. [23] had analysed the various emissions generations, equipment-wise auxiliary power consumption, station auxiliary power consumption, operation reliability. They had proved that CO₂ emission production is equivalent to coal consumption in the plant.

1.4 Energy efficiency improvements

Mahmoudi et al. [24] had identified approaches such as multivariate data analysis to improve the boiler performance and to decrease different emissions relating rate to the atmosphere. Joskow and Schmalensee [25] had analysed the thermal efficiency and consistency of electric generating units with coal burning, they had concluded that an increase in the steam pressure of generating units had led to advances in thermal efficiency. Kumar and Rao [26] had listed the various parameters like coal flow, feedwater flow, steam flow, airflow, excess air ratios, boiler, and turbine operation. They concluded that heat loss due to hydrogen is more than other heat losses. Franco and Casarosa [27] had explored the possibilities to increase the combined cycle plant efficiency. Results indicated that the hot reheat steam generator achieves 60% by using regenerator turbine exhaust gas temperature. Mandi et al. [28, 29] had studied the air-cooled and water-cooled condenser and cooling tower in a water-cooled condenser. They had concluded that with the less cooling tower makeup water the heat exchanger capacity of the condenser could be increased. Srinivas [30] had studied the dual pressure heat recovery steam generator (HRSG). He has concluded that optimization of combustion system possible at a temperature of 1400℃ with turbine blade cooling technology.

In this paper, we have analyzed a 660 MW supercritical thermal power plant considering various parameters viz. different plant load factors, different coal properties, and improving energy efficiency measures for equipment. We have also analyzed various methods to improve auxiliary power improvement of individual equipment like various boiler losses; excess air optimization techniques on different coal samples consequently studied the coal consumption and different emission levels generation from the plant.

The initial starting of the plant requires power and is supplied by external grids on a chargeable basis. The power could be distributed to equipment by station transformer which is located adjacent to the GT. Once power generation starts, power is available for running the equipment, this power is called unit auxiliary power. This power is tapped from the unit auxiliary transformer. The unit auxiliary power transformer supplies power to all equipment. The auxiliary power could be divided into two groups, in-house auxiliary power and Out-door auxiliary power or general auxiliary power.

The In-house auxiliary power equipment: Forced draft fans (FD), Boiler feed pumps (BFP), Primary air fans (PA), Induced draft fans (ID), Coal mills (pulverizes), and Condensate extraction pumps (CEP). Out-door or general auxiliary power is the power used for general tools such as auxiliary cooling water pumps (ACW), Circulating water pumps (CW), Demineralised water pumps, ash water pumps, Conveyors, Belts, Crushers, Common lighting available in the plant. Table 3 shows the major auxiliary power details.

Some power is always needed for the running of equipment; hence the specific power is defined as the ratio of power consumed by the equipment at motor terminals to the maximum generation.

SpecificAuxiliarypower $=\frac{(\mathrm{Pm} * 100)}{(\mathrm{Pl} * 100)}$

where, Pm = Measured power input to the motor, Pl= Measured P.L.F.

The specific auxiliary power of HT equipment is polynomial curve-fitted and is second-order concerning PLF.

Auxiliary Power (A.P) = 8.9*10-5 *PLF2-0.098162*PLF + 17.66993%

Table 4 shows the standard deviation for the second-order polynomial curve-fit is 0.978. It is showing a confidence level is more than 97%. It is appropriate and the scatter of data for the given units is within 2-3%.

Deviation in Auxiliary power $=\mathrm{C}_{0}+\mathrm{C}_{1} * \mathrm{PLF}+\mathrm{C}_{2} * \mathrm{PLF}^{2} \%$

where, C₀, C ₁, C ₂ coefficients and R² standard deviation given for all major equipment. The curve-fit second-order polynomial of variation of different specific auxiliary power is given in Table 4.

Deviation in Auxiliary power at various PLF’s in 660 MW.

unit $=\frac{\left(A P_{\mathrm{r}}-A P_{\mathrm{o}}\right) * 100 \%}{\left(A P_{\mathrm{r}}\right)}$

where, AP_r is the rated/design auxiliary power in kW, AP_o is the present operating auxiliary power in kW. The polynomial curve-fit for various specific auxiliary power with different PLF’s is in the range of 0.88-0.99% shown in Table 5. The attainable efficiency level of ID Fan is 88.07%, but in reality, it is low due to air leakage through APH, air enters through ducts, and hydrodynamic pressure drop.

In a 660 MW power plant under full load conditions, the deviation in different auxiliary power consumption and the deviation in auxiliary power is polynomial curve-fitted in the second-order derivative, Figure 10. From the deviation in auxiliary power consumption data (curve-fitted in second-order derivations), three constants and standard deviation could be found out.

Deviation in Auxiliary power of equipment $=\mathrm{D}_{\mathrm{o}}+\mathrm{D}_{1} * \mathrm{PLF}+\mathrm{D}_{2} * \mathrm{PLF}^{2} \%$

where, D₀, D ₁, D ₂ coefficients, and R² standard deviation given for all the major equipment. The curve-fitted second-order polynomial of variation of different specific auxiliary power is given in Table 6.

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Figure 10. Deviation of different equipment auxiliary power consumption with PLF (50-100%) at 660 MW plant

Table 3. Details about the primary auxiliary power equipment (in-house)

Table 4. Different auxiliary power curve-fit values with PLF (50-100%) at 660 MW plant

Table 5. Different auxiliary power values at different P.L.F

Table 6. Deviation of different auxiliary power curve-fit values with PLF (50-100%) at 660 MW plant

Table 7. Different specific energy consumption values at different PLF

The specific energy consumption for individual equipment as:

Specific energy consumption $=\frac{\text { Equipment power }}{\text { Feedwaterflow }} \mathrm{KW} /$ ton

The changes of specific energy consumption of all equipment are a second-order polynomial with different PLF’s:

Specific energy consumption $=\mathrm{E}_{\mathrm{o}}+\mathrm{E}_{1} * \mathrm{PLF}+\mathrm{E}_{2} * \mathrm{PLF}^{2} \%$

where, E₀, E ₁and E₂ are coefficients and R² is the standard deviation for all HT auxiliary equipment, Table 7.

The polynomial curve-fit values of standard deviation are in the range 0.728-0.982. The achievable efficiency levels for ID fan are 72.8%, for CEP is 88.9%, for FD fan is 95.2%, for Mill is 95.6%, etc. But in reality, the values are less due to incombustible air enters through APH and ducts which do not take part in the combustion. This air reduces the capacity of the ID fan.

The performance test was conducted on 2 units of 660 MW units. Two units were having a common station transformer where the station loads were distributed and having the same equipment such as ID Fans, BFP, PA Fans, FD Fans, and CEP, etc. Performance tests were conducted on Boiler and Turbine from PTC 4.1 and PTC 6.1. Blended coal having a 70:30 proportion was used as an input to the Boiler. The test was conducted for nearly 3 hours on full load. During the test period, the blowdown, soot blowing, and equipment changeover were halted to obtain an accurate result.

3.1 Detailed study on the HT- In-house auxiliary equipment

1. Induced draft fans are used to send flue gas from the furnace to the atmosphere and uphold negative draft inside the furnace (-200 to -220 Pa) consuming 0.64% of GEG at maximum continuous rating (MCR) conditions. This is equivalent to 2.23 tones of coal consumption and releases 2.09 tones of CO₂ emissions, 18.39 kg of SO₂ and 3.24 kg of NOx.
2. Forced draft fans supply air to the furnace through a wind box for effective combustion. Total 1501 tones of air supplied to furnace. The specific power consumption used for FD fans 0.26% of GEG at MCR conditions i.e., equivalent to 1.01 tones of coal consumption and release 1 ton of CO₂ emission, 12.22 kg of SO₂,7.40 kg of NOx.
3. Primary air fans supply primary air to the mill to lift pulverized coal which is powdered form, from mill mixing of both Primary air and coal powder goes to the furnace for combustion. Nearly 576 tones of air go to the furnace with coal powder at MCR. The specific power consumption for PA fans 0.57% of GEG - corresponding values of 2.325 tones of coal consumption and release 2.208 tones of CO₂ emission, 27 kg of SO₂, and 16 kg of NOx.
4. Mills are installed to provide the pulverized coal to the furnace for combustion. The specific auxiliary power for mill 0.15% of GEG -corresponding values of 620 kg of coal consumption/mill and release 589 kg of CO₂ emission,7.2 kgs of SO₂, and 4.38 kgs of NOx.
5. Condensate extraction pumps draw water from a hot well and send it to the deaerator through LP heaters. The specific auxiliary power used by Condensate extraction pump for 0.16% of GEG at MCR condition i.e., equivalent to 644.8 kg of coal consumption and release 612.56 kg of CO₂ emission,4.64 kg of SO₂, and 2.824 kgs of NOx.
6. Cooling water pumps draw water from the sea and sent to condenser for condensate cooling purpose. The specific auxiliary power used by the pump 3.93% of GEG at MCR condition i.e. equivalent to 1612 kg of coal consumption and release 1531.4 kg of CO₂ emission,11.606 kgs of SO₂, and 7.060kgs of NOx.
7. The total coal consumption for auxiliary is 19.027 tones which is the equivalent release of CO₂ emission 18.075 tonnes,136 kg of Sox and 86 kgs of NOx.
8. The auxiliary power is affected by the PLF of power units. The auxiliary power rises when PLF decreases, and it would increase when PLF increases. The total specific auxiliary power changes are curve-fitted with a second-order polynomial equation with PLF.

Power plant operating at 60-100% maximum continuous rating condition, could reduce auxiliary power consumption from 5.95% to 4.76% in a 660 MW supercritical thermal power plant. At this 60-100% maximum continuous rating condition, the auxiliary power is reduced by 68.80 MU/year causing the reduction of CO₂ emissions by 65,300 t/y. After optimizing the excess air and selection of low ash coal save power consumption by 97 kW/hour which is an equivalent reduction of CO₂ by 0.1018 t/y and overhauling of plant equipment reduces hydrodynamic resistance of flue gas which reduces the auxiliary power by 0.11% of gross energy generation. By maintaining the performance of individual equipment, optimum excess air, and controlling furnace ingress through proper maintenance, the auxiliary power is reduced by 1.05% of gross energy. The overall reduction of auxiliary power from various methods could be 1.19% i.e., equivalent to a CO₂ reduction of 65,300 t/y and added surplus power of 7.85 MW/hour into the grid through the energy conservation techniques.