Dr. Manam Ravindra
@acet.ac.in
Head of the EEE Department
Aditya College of Engineering and Technology
Dr. Manam Ravindra is an Associate Professor in the Department of Electrical and Electronics Engineering at Aditya College of Engineering and Technology Surampalem, India. He completed his PhD at JNTU Kakinada. He has more than 25 publications, which are published in reputed journals indexed in the Scopus and Web of Science databases. His areas of interest include, Electrical Vehicles, Energy Management, Power System State Estimation, Power systems operation and control and Electric power distribution systems.
EDUCATION
PhD In Power Systems from JNTU Kakinada
M Tech in Power System Control and Automation from JNTU Kakinada
B.Tech in Electrical and Electronics Engineering from Aditya Engineering College Surampalem.
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Energy Engineering and Power Technology, Renewable Energy, Sustainability and the Environment, General Energy
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
M. Laskhmi Swarupa, V. Ganesh Kumar, K. Sree Latha, Manam Ravindra, and B. Praveen Kumar
Universal Wiser Publisher Pte. Ltd
To maintain system security and other essential parameters like reliability and quality, continuous monitoring of the system is very important. Considering the distribution network, state estimation (SE) methods can be adopted. The purpose of the method is to identify and estimate unknown variables based on the online measurements of test data. The primary objectives considered in this paper are: To choose the exact SE method and the artificial neural network (back propagation algorithm), which can be used for determination in the islanding mode of distribution network states, the composite load model is considered for the estimation of states and further enhancement. By adopting the system, state variables in terms of error are measured in the 12-bus distribution network with precise measurements and compared with practical values. The SE proposed includes results with the load flow backward-forward sweep method to satisfy the system state variables. Numerical results indicate that the model performs better for error measurement data with states and in the case of state forecasting.
Durgamadhab Swain, Meera Viswavandya, Ritesh Dash, Kalvakurthi Jyotheeswara Reddy, Dhanamjayulu Chittathuru, Arunkumar Gopal, Baseem Khan, and Manam Ravindra
MDPI AG
The deployment of a static synchronous compensator within a microgrid can facilitate voltage and reactive power regulation, leading to enhanced stability and reliability. Within a microgrid setting, the effectiveness of a STATCOM in balancing the power supply is influenced by several factors, including the system configuration, the operating conditions, and the specific requirements of the power grid. The capacity, response time, and magnitude of system disturbances also play a role in determining the STATCOM’s ability to balance the power supply. To ensure the successful integration of a STATCOM within a microgrid, coordinating the control system with other distributed energy resources (DER), especially when multiple control strategies are employed, can be a challenging task. Therefore, a meticulously designed control system is indispensable to guarantee the microgrid’s efficient and effective operation. The use of GA in LSTM tuning can accelerate the process of identifying the optimal hyperparameters for a specific task, obviating the need for time-consuming and computationally expensive grid searches or manual tuning. This method can be particularly advantageous when handling large data sets and complex models. In this paper, an attempt has been made to model the STATCOM to communicate with the microgrid, tuned using LSTM–GA, for the effective calculation of real and reactive power support during grid disturbances.
H. Jeevan Rao, N. Nagabhooshanam, D. Sendil Kumar, Santosh Kumar Sahu, Rajesh Verma, Gandeti Jyothirmai, Manam Ravindra, and V. Mohanavel
Wiley
AbstractIn the current work, light weight epoxy bio‐composites are created for low‐cost technological applications using luffa aegyptiaca fiber and biochar particles derived from coco husk (CHB). This study aims to evaluate the effects of CHB particles added at different concentrations (3 vol% and 5 vol%) on the dynamic mechanical, ballistic and tribology behavior of epoxy composites constructed from luffa aegyptiaca fiber with different fiber loading (20%, 30% and 40 vol%). The composites are prepared using hand layup process provided with post curing operation. The combination of 3 vol% CHB particles and 40 vol% luffa aegyptiaca fiber having the improved viscoelastic properties by means of high storage modulus (5.05 GPa) and low loss factor (0.31). Moreover, this composite shows better ballistic properties in terms of low velocity impact energy (17.1 J). The optical image of impact damage behavior shows minimum damage of impactor on the composite and penetration effect found to be lower. This luffa aegyptiaca fiber reinforced epoxy composite also shows the lowest value of coefficient of friction (COF) with 0.48 and the lowest specific wear rate of 0.011 mm3/Nm. These epoxy composites made from luffa aegyptiaca fiber and CHB particles may be useful in a variety of engineering applications that can use materials for manufacture sporting goods, home furnishings, food packaging, and transportation.
Ravindra Manam, Ramesh Adireddy, Lakshmi Kambampati, Manoz Kumar Reddy Karri, Tata Rao Donepudi, and Srinivasa Rao Rayapudi
IEEE
This paper presents a Pattern Search (PS) algorithm for optimal placement of Micro-Phasor Measurement Units (M-PMUs) in a distribution network to obtain complete observability through which security of network can be attained. By the distribution state estimation process, these M-PMU measurements can help to estimate the state of every node in the network. The pattern search algorithm is a nonlinear, constrained procedure used to optimize network locations for M-PMU placement. Redundancy bus nodes in the feeder network are considered in the optimization process to minimize PMU locations. The locations of M-PMUs with and without radial buses are compared. A redundancy index (RI) at the node and a complete network observabilty index (CNOI) for the entire network are proposed to assess network observabilty. The proposed indices can show whether the system is completely observable or not. Test cases that are MATLAB-programmed include the IEEE-13, 33, and 69 feeder networks. The effectiveness of the findings in the optimization of nonlinear constraints is shown by comparison with other widely used techniques.
Manam Ravindra, Donepudi Tata Rao, Rayapudi Srinivasa Rao, Adireddy Ramesh, and Karri Manoz Kumar Reddy
Springer Nature Singapore
Arigela Satya Veerendra, Manam Ravindra, Adireddy Ramesh, Karri Manoz Kumar Reddy, and Chavali Punya Sekhar
Wiley
AbstractFollowing years, electric vehicles (EVs) are promising technology for shifting scattered exhaust emissions in mega‐cities to integrated power plants in rural areas, especially in urban areas. Transport sector electrification and increased popularity of EVs make scientists and researchers, search for charging stations. The ideal position, charge scheduling, and developed charging infrastructure are the primary concern for the large‐scale deployment of EVs. This paper describes the possible demand for EVs charging station infrastructure and challenges in the Indian situation. Along these lines, this study also provides the research community with the latest developments and research findings of charging infrastructure for EVs in India.
Ravindra Manam, Ravindra Sangu, Lakshminarayana Pamidi, and Manoz Kumar Reddy Karri
Springer Science and Business Media LLC
Ramesh Adireddy, Kunche Nanibabu, M. Ravindra, and K.V.S. Ramachandra Murthy
Elsevier BV
Ramesh Adireddy, Boddu Sai Deepak, M. Ravindra, and K.V.S. Ramachandra Murthy
Elsevier BV
Srinivasa Rao Veeranki, Srinivasa Rao Rayapudi, and Ravindra Manam
Springer Singapore
M. Ravindra, R. Srinivasa Rao, V. Srinivasa Rao, N. Praneeth, and Vasimalla Ashok
Springer Singapore
Manam Ravindra, Rayapudi Srinivasa Rao, and Vonteddu Shanmukha NagaRaju
Springer Singapore
M. Ravindra and R. Srinivasa Rao
IEEE
This paper presents a new Binary Integer Linear Programming (BILP) approach considering modeling of zero injection constraints for optimal allocation of PMUs in the network and to generate dynamic state estimation solution in presence of load changes. Zero injection bus constraint modeling is considered to minimize the number of PMUs in the system. To find the dynamic behavior of power system in presence of load changes, a dynamic state estimation method integrating PMU and conventional measurements is proposed. The proposed dynamic state estimation method with optimal PMU allocations is compared with traditional Weighted Least Squares (WLS) state estimation method in presence of load changes. MATLAB simulations carried out on IEEE 14, 30, 57 and 118 bus systems and their results show the effectiveness of proposed method.