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Pulivarthi Nageswara Rao
Department of Electrical Electronics and Communication Engineering, Gandhi Institute of Technology and Management (Deemed to be University), Visakhapatnam 530045, Andhra Pradesh, India

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Review
Published: 27 November 2020 in Energies
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Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

ACS Style

Amit Kumer Podder; Sayemul Islam; Nallapaneni Manoj Kumar; Aneesh A. Chand; Pulivarthi Nageswara Rao; Kushal A. Prasad; T. Logeswaran; Kabir A. Mamun. Systematic Categorization of Optimization Strategies for Virtual Power Plants. Energies 2020, 13, 6251 .

AMA Style

Amit Kumer Podder, Sayemul Islam, Nallapaneni Manoj Kumar, Aneesh A. Chand, Pulivarthi Nageswara Rao, Kushal A. Prasad, T. Logeswaran, Kabir A. Mamun. Systematic Categorization of Optimization Strategies for Virtual Power Plants. Energies. 2020; 13 (23):6251.

Chicago/Turabian Style

Amit Kumer Podder; Sayemul Islam; Nallapaneni Manoj Kumar; Aneesh A. Chand; Pulivarthi Nageswara Rao; Kushal A. Prasad; T. Logeswaran; Kabir A. Mamun. 2020. "Systematic Categorization of Optimization Strategies for Virtual Power Plants." Energies 13, no. 23: 6251.

Journal article
Published: 20 October 2020 in Energies
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Bearingless motor development is a substitute for magnetic bearing motors owing to several benefits, such as nominal repairs, compactness, lower cost, and no need for high-power amplifiers. Compared to conventional motors, rotor levitation and its steady control is an additional duty in bearingless switched reluctance motors when starting. For high-speed applications, the use of simple proportional integral derivative and fuzzy control schemes are not in effect in suspension control of the rotor owing to inherent parameter variations and external suspension loads. In this paper, a new robust global sliding-mode controller is suggested to control rotor displacements and their positions to ensure fewer eccentric rotor displacements when a bearingless switched reluctance motor is subjected to different parameter variations and loads. Extra exponential fast-decaying nonlinear functions and rotor-tracking error functions have been used in the modeling of the global sliding-mode switching surface. Simulation studies have been conducted under different testing conditions. From the results, it is shown that rotor displacements and suspension forces in X and Y directions are robust and stable. Owing to the proposed control action of the suspension phase currents, the rotor always comes back rapidly to the center position under any uncertainty.

ACS Style

Pulivarthi Nageswara Rao; Ramesh Devarapalli; Fausto Pedro García Márquez; Hasmat Malik. Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor. Energies 2020, 13, 5485 .

AMA Style

Pulivarthi Nageswara Rao, Ramesh Devarapalli, Fausto Pedro García Márquez, Hasmat Malik. Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor. Energies. 2020; 13 (20):5485.

Chicago/Turabian Style

Pulivarthi Nageswara Rao; Ramesh Devarapalli; Fausto Pedro García Márquez; Hasmat Malik. 2020. "Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor." Energies 13, no. 20: 5485.

Journal article
Published: 12 June 2020 in Applied Sciences
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The bearingless concept is a plausible alternative to the magnetic bearing drives. It provides numerous advantages like minimal maintenance, low cost, compactness and no requirement of high-performance power amplifiers. Controlling the rotor position and its displacements under parameter variations during acceleration and deceleration phases was not effective with the use of conventional controllers like proportional–integral–derivative (PID) and fuzzy-type controllers. Hence, to get the robust and stable operation of a bearingless switched reluctance motor (BSRM), a new robust dynamic sliding mode controller has been proposed in this paper, along with a sensorless operation using a sliding ode observer. The rotor displacement tracking error functions and speed tracking error functions are used in the designing of both proposed methods of the sliding mode switching functions. To get a healthy and stable operation of the BSRM, the proposed controller’s tasks are divided into three steps. As a first step, the displaced rotor in any one of the four quadrants in the air gap has to pull back to the centre position successfully. The second step is to run the motor at a rated speed by exciting torque phase currents, and finally, the third step is to maintain the stable and robust operation of the BSRM even under the application of different loads and changes of the motor parameters. Simulation studies were conducted and analysed under different testing conditions. The suspension forces, rotor displacements, are robust and stable, and the rotor is pulled back quickly to the centre position due to the proposed controller’s actions. The improved performance characteristics of the dynamic sliding mode controller (DSMC)-based sliding mode observer (SMO) was compared with the conventional sliding mode controller (SMC)-based SMO.

ACS Style

Pulivarthi Nageswara Rao; Nallapaneni Manoj Kumar; Sanjeevikumar Padmanaban; M. S. P. Subathra; Aneesh A. Chand. A Novel Sensorless Approach for Speed and Displacement Control of Bearingless Switched Reluctance Motor. Applied Sciences 2020, 10, 4070 .

AMA Style

Pulivarthi Nageswara Rao, Nallapaneni Manoj Kumar, Sanjeevikumar Padmanaban, M. S. P. Subathra, Aneesh A. Chand. A Novel Sensorless Approach for Speed and Displacement Control of Bearingless Switched Reluctance Motor. Applied Sciences. 2020; 10 (12):4070.

Chicago/Turabian Style

Pulivarthi Nageswara Rao; Nallapaneni Manoj Kumar; Sanjeevikumar Padmanaban; M. S. P. Subathra; Aneesh A. Chand. 2020. "A Novel Sensorless Approach for Speed and Displacement Control of Bearingless Switched Reluctance Motor." Applied Sciences 10, no. 12: 4070.