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Technical Study:"Improvement of the ESP (Electrostatic Precipitator) Performance"

November, 2014

By applying Computational Fluid Dynamics (CFD) modeling optimization and flue gas conditioning in one of NTPC plant as show-case project of EEC.

NTPC had submitted a proposal to EEC regarding carrying out Computational Fluid Dynamics (CFD) Modelling of ESP in one of the generating unit of 500 MW at Ramagundam STPS.

NTPC owns several pulverized coal fired power plants of the 500 MWe class equipped with conventional Electrostatic Precipitator  (ESP). The exemplary design value for the dust concentration in the clean gas is 42 mg/Nm³ at full load whereas the measured present value is 110-130 mg/Nm³ with 35-40% ash content in the coal.

For this reason, NTPC intends to improve the collection efficiency of the ESP by using advanced diagnostics such as Computational Fluid Dynamics Modeling (CFD) and SO3 flue gas conditioning guided and supported by best practice experiences gained from implemented projects.

As a partner of EEC, VGB took up the proposal and set-up an ESP-team consisting of personnel from VGB and STEAG Energy Services (SES). SES has the competences and expertise in optimizing ESP-performance (CFD modeling and SO3 conditioning);

CFD modeling is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows. Computers are used to perform the calculations required to simulate the interaction of liquids and gases with surfaces defined by boundary conditions.



Excellence Enhancement Centre (EEC) and NTPC, EEC set up by Central Electricity Authority under Indo-German Energy (IGEN) program to facilitate performance improvement in Indian power sector have signed an MoU for a joint research project. Thomas Joseph, ED, NTPC-NETRA, signed the MoU along with B.K Sharma, Member Secretary, EEC & Chief Engineer (C&E), CEA, in presence of Shri Major Singh, Vice President, EEC & Member (Planning), CEA, Shri A. K. Jha, Director (Technical), NTPC and other senior officials from EEC, CEA and NTPC. 


SO3 conditioning of the flue gas is a process in which the surface conductivity of the particles in the flue gas are improved in order to reach a better dust removal in the ESP. Technologically, SO3 flue gas conditioning plant consists of a container, in which sulphur will be burned to SO2 and converted to SO3 in a catalyst. SO3 together with air will be injected through injection lances into the flue gas duct. SO3 will be condensed at the outlet of the lances so that the dust particles will be thoroughly charged. This increases the conductivity of the dust for a better separation in the ESP.

Through the improvement of the ESP performance, the particulate emissions in general will decrease and in this way the dust concentration entering the flue gas path and being emitted through the stack will be reduced substantially to the immediate benefit of the environment.

ESP performance Improvement using CFD modeling was completed by NTPC-NETRA with the support of VGB/EEC.
Initial measurements was carried out by NTPC-NETRA with the support of VGB/EEC, based on the input provided by VGB/EEC on the CFD model, the modifications along with fabrication drawings were developed by NTPC.
The modifications have been implemented in the last overhauling of Unit no. 4 at Ramagundam STPS (December,2017 - January,2018). The SPM measurement is planned after few months of stable operation to verify the predicted benefits.
Based on the results, it is planned to encourage state utilities to undertake similar work.  


Environmental and efficiency improvement of power plant performance is an essential goal for the years to come. Effective particulate and ash removal in coal fired power plants by Electrostatic Precipitators is a must for environmental compliant and commonly accepted operation. In order to enhance and support this goal a CFD modeling for an exemplary ESP unit will be carried out. In this way the flow conditions and the dust concentration will be analyzed and potential for optimization will be identified.