Innovations in energy management of induction machine based industrial plants (PhD)

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dc.contributor.advisor Dr. Bharat Singh Rajpurohit
dc.contributor.author Grewal, Gurinderbir Singh
dc.date.accessioned 2021-03-10T08:08:26Z
dc.date.available 2021-03-10T08:08:26Z
dc.date.issued 2017-09-20
dc.identifier.uri http://hdl.handle.net/123456789/414
dc.description A thesis submitted for the award of the degree of Doctor of Philosophy under the guidance of Dr. Bharat Singh Rajpurohit (Faculty, SCEE). en_US
dc.description.abstract The non-intrusive in-situ efficiency estimation of induction machines (IMs) in real industrial environment is given due consideration and its possibilities are thoroughly investigated. The non-intrusiveness refers to measurement of electrical input voltages and currents at IM terminals only. This thesis develops the techniques for estimating the efficiency of IM in a non-intrusive manner for balanced/unbalanced power supplies. Also, energy auditing case studies of two industrial plants is undertaken to reduce consumption of electrical power and enhance savings. Overall work has been completed in three sections. First section is the study of numerous methods of efficiency estimation of IM and different standards applied so far. In this section, the mathematical modeling of IM is done in D-Q reference frame. Efficiency calculation of IM is done in stationary reference frame. The efficiency estimation of in-situ IM is accomplished through the development of low cost non-intrusive air-gap torque method by doing modifications to original airgap torque method based on air-gap torque equations employing line-to-line voltages and two phase currents with sufficient accuracy and least intrusion level. Speed estimation of IM rotor is accomplished by model reference adaptive mechanism which utilizes rotor flux error vector as tuning signal for speed estimation for IM drives in the speed adaptation mechanism. Efficiency estimation is performed for both balanced and unbalanced conditions. In the second section, population based algorithm i.e. cuckoo search algorithm (CSA) is proposed for efficiency estimation of in-situ IM which is capable of dealing with balanced/unbalanced voltages. The proposed technique is non-intrusive in nature and needs least measurements like two line voltages and currents along with nameplate data of IM. Also, gravitational search based algorithm (GSA) is proposed for efficiency estimation of in-service IMs which handles unbalanced/unbalanced voltages and gives better results than CSA. These proposed techniques don’t alter any operating condition of IM. In the third section analysis for energy auditing performed for two industrial plants i.e. Jindal Steel Plant (JSP) and Sohna Woolen Mill (SWM) to reduce their energy consumption is presented. This task is accomplished by analyzing the replacement of IMs giving poor efficiencies by energy-efficient IMs of suitable ratings. In JSP, rescheduling of loads on power transformers is done to reduce the losses and burden on insulation of over-loaded transformer. This enhances energy savings as well. Also, power factor improvement is suggested for JSP. During the process of energy auditing, the need of device for efficiency estimation of IM for any loading condition is felt since lot of time is consumed in measurements of electrical input quantities. Conventional methods of efficiency estimation need de-coupling of IM from drive. Therefore, a low cost nonintrusive handheld device is fabricated for evaluating IM efficiency. This device has PIC 18F4520 micro-controller which is programmed as per non-intrusive air-gap torque method. This handheld device is implemented for efficiency estimation of IM in balanced/unbalanced voltages. en_US
dc.language.iso en_US en_US
dc.publisher IITMandi en_US
dc.subject Municipal DSM en_US
dc.subject Cuckoo Search Algorithm Technique en_US
dc.title Innovations in energy management of induction machine based industrial plants (PhD) en_US
dc.type Thesis en_US


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