POWER FACTOR IMPROVEMENT IN THE RUBBER INDUSTRY USING FUZZY LOGIC

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GRD Journals | Global Research and Development Journal for Engineering | International Conference on Innovations in Engineering and Technology (ICIET) - 2016 | July 2016

e-ISSN: 2455-5703

Power Factor Improvement in The Rubber Industry using Fuzzy Logic 1P.Loganthurai 2L.Jayamala 1

Professor 2Student Department of Electrical and Electronics Engineering 1,2 K.L.N College of Engineering Pottapalayam , Tamilnadu, India 1,2

Abstract Indian industry is paying one of the highest power tariffs in the world due to the poor quality and lack of power generation, transmission and distribution management. Recent advancements for higher power generation, lesser transmission and distribution cost and saving of energy can benefit significantly by improving the power system through energy efficiency at all levels. The electric billing is a two part tariff, the first part is unit (kWh) cost and the second part is maximum demand (kVA) cost. The maximum demand cost can be reduced by improving power factor. The overall power factor of modern industrial plants is low because of induction motors absorbing more reactive power. When power factor is improved, the reactive power necessary to supply the useful (real) power is automatically reduced. This results in the reduction of maximum demand (kVA) of the entire industrial plant. All the H.T (High Tension) consumers should maintain the power factor above 0.95 in order to avoid the penalization in their electricity bill. In many industries, they are maintaining good power factor (PF) at the incoming terminal of power lines using automatic power factor corrector but measuring power factor at the load side, it is low. Thus, in this proposed work the distributed power factor correction method is used to maintain good power factor at the load side. To select the suitable size of capacitor for compensating the reactive power requirement of induction motors, the Fuzzy Logic (FL) has been used. Keyword- DSM, Power factor improvement, Fuzzy logic __________________________________________________________________________________________________

I. INTRODUCTION In recent years availability of power in India has both increased and improved but demand has consistently outstripped supply and substantial energy and peak shortages prevailed in 2009-10. There are also various estimates of 25000 to 35000 MW of power being produced by diesel generation to meet the deficits [1]. Electricity shortage is not the only problem. Its spread is an equally serious issue. Although such an approach is essential, there is growing concern about other aspects of power generation such as social, environmental and technological benefits and consequences of the energy source selection. Accordingly, energy audit is an effective means assisting facility managers to develop plans and to achieve goals in energy saving. Moreover, the audit can eliminate the barriers of energy efficiency even in case of inadequate information [2]. Electrical energy management (EEM) is a topic that has reached specific concern in the twenty- first century due to its contribution to economic development and environmental advancement [3].

II. DEMAND SIDE MANAGEMENT Demand Side Management (DSM) refers to a process by which electric utilities, in collaboration with consumers, achieve predictable and sustainable changes in electricity demand. These changes are effected through a permanent reduction in demand levels through energy efficiency as well as time related reductions in demand levels through load management. The practice of Demand Side Management has evolved over the past three decades in response to lessons learned from implementation in different global settings, and also in response to the changing needs of restructured power markets [4]. There are a number of ways to incentives demand reduction and energy conservation. These include,  Tariffs  Technology  Rebates  Quotas  Customer education etc. DSM programs that emphasize tariffs are aimed at introducing a negative slope in the demand curve in order to let demand and supply balance out at a reasonable price of electricity during tight market conditions[5]. Programs involving demand response to tariffs fall into one of two categories:  Load curtailment programs that pay the customer for reducing peak load during critical times

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