Journal of Energy Technologies and Policy www.iiste.org ISSN 2224-3232 (Paper) ISSN 2225-0573 (Online) Vol.5, No.2, 2015 84 On Optimization of Air Pollution and Electricity Production of Thermal Power Plants of Delhi using Goal Programming Rajesh Dangwal 1 Arvind Kumar 2 Vivek Naithani 1* 1.Deptt. of Mathematics, H.N.B.Garhwal University. Pauri Campus 2. Deptt. Of Mathematics, ACC Wing, Indian Military Academy, Dehradun dangwalrajesh@yahoo.co.in; ark62@gmail.com; *vivekmassive@gmail.com Abstract Air pollution is a serious problem in today’s rapidly developing world. Burning of fossil fuels has been the source of air pollution since ages. Coal is a major source of electricity production in India. About 56% of total electricity produced is from Thermal Power Plants (TPPs). In Delhi we have taken 5 TPPs producing about 2800 MW of energy catering to the desire of the nation for this study.Sulphur dioxide (SO 2 ), Oxides of Nitrogen (NO x ) , Total Suspended particulate matter (TSPM) are the main pollutants emitted from TPPs. Due to burning of coal in huge amount in TPPs a large amount of pollutants is emitted in the air. But on the contrary we cannot stop this process completely as coal is efficient as well as easily available resource in this day and other non conventional sources like solar, tidal, wind power etc. are in their infancy in the country. In this paper we are trying to optimize pollutants of air emitted from TPPs and electricity production in aggregate from 5 TPPs working in Delhi using a Goal Programming (GP) model. Keywords: Thermal Power Plant (TPP), SO 2 , NO x , TSPM, Optimization, Goal Programming (GP) 1. Introduction Air pollution is a serious problem which has taken a serious shape with rapid industrialization. Generation of pollutants of air from burning of fossil fuels comprise a major part of the total air pollution. Coal, petrol, diesel, kerosene, etc. are main fuels which are extensively used in today’s developing world. Fossil fuels occupy an important place among all sources of energy due to high calorific value and extensive and easy use. Apart of CO 2 the other harmful gases and pollutants released in air are Sulphur dioxde (SO 2 ), oxides of Nitrogen (NO x ) and Total Suspended particulate matter (TSPM). Today a major part of total electricity produced is by burning fossil fuels in thermal power plants (TPPs) which although is convenient and cheap than other non conventional sources but on the contrary is equally harmful for the quality of ambient air. In India coal and other fossil fuels are major source of energy in different sectors like domestic, industrial, power production, etc. A huge amount of coal and other fossil fuels are burnt in TPPs in the process of production of electricity which is causing huge amount of air pollution. These major qualitative pollutants are causing huge damage to the environment and health of people. There are a number of ways to control the quantity of these pollutants in ambient air like use of precipitators, reduce consumption of fossil fuels, treatment of gaseous effluents from industries before allowing them to go into air, etc. It is also estimated that increase in the use of non conventional sources like solar, tidal, wind energy etc. will definitely reduce this air pollution but in our country it is still in its infancy. Its administration is a lengthy process in our country and it is costly and not in easy access to the masses. Thus it becomes necessary to find out some means that may help in reduction of this kind of air pollution without actually effecting the production of electricity in the country. 2. Goal Programming Goal programming (GP) is an important analytical approach devised to solve many real world problems, where targets have been assigned to all attributes and where decision makers (DM) are interested in minimizing the non achievement the corresponding goal. [Chin Nung Laio]. GP was first introduced by Charnes and Cooper (1961) and further developed by Lee (1972), Ignizio (1976), Tamiz et.al. (1998), etc. Generally GP minimizes undesired deviations from target values. In this method the DM can consider many goals simultaneously during the search for compromise solution and is supported by Mathematical Programming Optimization Potential (Martel and Aouni, 1998). GP is a powerful tool which draws upon the highly developed and tested techniques of LP but provides a simultaneous solution to a complex system of competing objectives (Banashri Sinha and N Sen, 2011). GP is a mathematical programming technique which treats the constraints of linear programming problem as their goal. Linear programming as a goal in the objective function, optimization means coming as close as possible to achieve these goals in order of priority by the decision maker. Goal programming is applicable to single or multiple goal although it is a greater usefulness occurs when the multiple goal are conflicting and cannot satisfied simultaneously. Goal Programming is a fancy name for a very simple idea: the line between objectives and constraints