Qualification: 
Ph.D, MPhil, MSc, B.Ed., BSc
r_subramani@blr.amrita.edu

Dr. R. Subramani currently serves as Assistant Professor (Sr. Gr.) at the department of Mathematics, School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru Campus. He was conferred with a Ph.D. in Mathematics from VIT University, Chennai. His areas of interest include Advanced Optimization Techniques and Operations Research. He is with Amrita since 2018. He did his M.Sc. from Madras University. He has teaching experinece of 2 years and research experience of 4 years. He is also qualified UGC SET.  

Education

  • 2017: Ph. D.
    VIT University
  • 2014: M.Phil.
    St. Peter’s University 
  • 2012: M.Sc.
    University of Madras
  • 2010: B.Ed.
    TNTEU
  • 2009: B.Sc.
    University of Madras

Publications

Publication Type: Journal Article

Year of Publication Title

2019

R. Subramani and Vijayalakshmi, C., “Implementation of Optimal Scheduling Model for Power Flow System”, International Journal of Computer Aided Engineering and Technology, vol. 11, no. 2, pp. 151 – 162, 2019.[Abstract]


This paper mainly deals with the development of an energy management model using a supervisory control and data acquisition (SCADA) system. A predictive controller is implemented above the centralised SCADA platform. The distribution networks have been focused by a monitor, control and maintain equipment in the substations to reduce the operating cost. This research proposes a new energy management model that enables a flexible and also efficient operation of various power plants. The distribution control centre (DCC) is being monitored and controlled by SCADA systems and the DCC has become an important energy efficient policy concept. Based on the numerical calculations and graphical representations the renewable energy sources in both configurations, is independent of the enduring or intermittent main energy resource availability, which can lead to effective production.

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2018

C. Vijayalakshmi and R. Subramani, “Stochastic Behavior for the Reliability and Cost Benefit Analysis in a Petrochemical Industry”, International Journal of Pure and Applied Mathematics, vol. 118, no. 23, pp. 383 – 390, 2018.[Abstract]


This paper mainly deals with the reliability and cost benefit analysis of Inert Gas units in a petrochemical industry. Network reliability evaluation using probability expressions have been briefly discussed by various authors.In this paper, the stochastic behaviour of the Inert Gas is being analyzed. Methodology for reliability assessment is obtained by using the updated techniques for two Inert Gas units.

Reliability study, failure analysis, cost function for starting the new inert gas unit have been discussed. The causes for failure and remedial solutions are suggested along with numerical calculations and graphical representations.

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2018

R. Subramani and Vijayalakshmi, C., “Augmented Lagrangian Algorithm for Hydrothermal Scheduling”, EAI Endorsed Transactions on Energy Web and Information Technologies, vol. 5, no. 18, pp. 1 – 7, 2018.[Abstract]


This paper mainly deals with a new algorithm for solving hydrothermal scheduling problem with transmission and environmental constraints using Augmented Lagrangian(AL) method. Hydrothermal scheduling is a most important task in power management system. Transmission capacity and environmental constraints are relaxed by using Lagrangian multipliers. The existing methods are provided suboptimal solutions from the computational burden due to the large number of variables involved in the problem. This paper ensures efficient technique that involves a reduced number of decision variables for hydrothermal scheduling to reduce the total operating cost through AL method. The ultimate aim of hydrothermal scheduling is to ensure the optimal generation in both hydro and thermal units in order to fulfill the demands over a scheduled horizon. In this paper optimal hourly schedule for power generation in hydrothermal scheduling system applying Augmented Lagrangian Relaxation (ALR) technique.

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2017

R. Subramani and Vijayalakshmi, C., “Design and Analysis of Lagrangian Algorithm for Power Flow System using Renewable Energy Resources”, Indonesian Journal of Electrical Engineering and Computer Science, vol. 7, no. 2, pp. 348 – 355, 2017.[Abstract]


This paper mainly deals with the implementation of an Lagrangian Relaxation (LR) technique through a Supervisory Control and Data Acquisition (SCADA) system. Maintaining Power Station is not an easy task which to achieve its demand such as regulating inputs monitoring energy losses. In this paper we have introduced novel SCADA based decentralized approach to minimize the loss of the system and optimize the total generation cost. Due to the nonlinearities of Electricity demand and scheduling time, the problem is not solvable with the usual optimization techniques. For getting appropriate solution LR technique has been formulated as a nonlinear programming problem with respect to optimal energy constraints. Based on the numerical calculations and graphical representations the renewable energy sources are optimally allocated in individual and hybrid configurations, which leads to effective production.

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2017

R. Subramani and Vijayalakshmi, C., “A Review on Advances Optimization Techniques”, ARPN Journal of Engineering and Applied Sciences, vol. 11, no. 19, pp. 11675 – 11683, 2017.[Abstract]


This paper mainly deals with the review on the various advanced optimization techniques. Optimization reveals significance advances in computing systems and it has become the most promising techniques for a variety of engineering applications. This paper highlights the various techniques such as evolutionary techniques, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to enhance the search process by improving the diversity, and the convergence toward the preferred solution have been analysed. A comparative study between the single and multi-objective based Optimization techniques including GA, PSO and Hybrid are presented. This comparison will be very helpful for industries to determine the optimal parameters and improve the process and quality of products.  A variety of objective functions and its formulations are presented. Lagrangian relaxation is a tool to find upper bounds on a given arbitrary maximization problem. The main theme of this review is that the LD is naturally applied for a wide class of combinatorial algorithms which leads to get a significant solution.  Among all the traditional optimization techniques, in recent years, heuristic algorithms are mostly applied to solve most of the combinatorial problems.  Optimization  algorithms  can  lead  to appropriate solution for the real time applications.

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2016

R. Subramani and Vijayalakshmi, C., “Implementation of an Optimization Model for Pump Scheduling”, International Journal of Pure and Applied Mathematics, vol. 109, no. 5, pp. 41 – 49, 2016.[Abstract]


This paper mainly deals with the design of water distribution networks. Maintaining water distribution system is not an easy task which involves scheduling pumps, maintaining proper water levels for distribution, providing appropriate quality of water to the customer based on their essential quantity and pressure. Due to not linearities of the size of water distribution networks and planning horizons this problem is not solvable easily. In this paper we have proposed a model that can give a novelty for optimizing pump schedule and its essential cost in water distribution networks. In order to get appropriate solutions a Lagrangian model has been proposed for a non-linear mixed integer programming problem. Based on this the energy sources leads to an efficient distribution.

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2016

R. Subramani and Vijayalakshmi, C., “Design of Lagrangian Decomposition model for Energy Management System”, International Journal - Smart Innovation, Systems and Technologies, vol. 49, pp. 353 – 361, 2016.[Abstract]


This paper mainly deals with the design and analysis of an Energy Management model using a SCADA (Supervisory Control and Data Acquisition) system. Each power system is restricted by its applicable control authority, forming a decentralized structure by using consistent network. A central optimal powerflow problem is decomposed into distributed subproblems to obtain the optimal solution. A new energy management model is designed which enables aflexible and efficient operation of various power plants. Based on the numerical calculations and graphical representations the renewable energy sources in both configurations is independent of the enduring or intermittent main energy resource availability, which leads to effective production.

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2015

R. Subramani and Vijayalakshmi, C., “Design and Analysis of Lagrangian Decomposition Model”, Global Journal of Pure and Applied Mathematics, vol. 11, no. 4, pp. 1859- 1871, 2015.[Abstract]


This paper mainly deals with design of Lagrangian decomposition algorithm. Decomposition algorithms are analyzed with respect to various parameters and conditions. Dual decomposition, and more generally Lagrangian relaxation, is a classical method for combinatorial optimization; it has recently been applied to several inference problems. Lagrangian Relaxation (LR) technique decomposes the optimization problem into subproblems; Lagrangian subproblems give the optimal solutions for the optimization problem. The aim of this paper is to identify the control and uncontrolled parameters of the various decomposition techniques which are framed as equality, inequality constraints. Particularly the Lagrangian multipliers added in the objective function of the Lagrangian problem which is acting as “penalty factors”, based on the parameters of the system. It is compared with the other decomposition techniques such as primal decomposition, dual decomposition. A main theme of this paper is that Lagrangian relaxation is obviously applied in conjunction with a wide class of combinatorial algorithms, allowing inference in models that provides the appropriate optimal solutions.

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Publication Type: Conference Proceedings

Year of Publication Title

2017

R. Subramani, “Solution Approaches for Unit Commitment Problems – Review”, International Conference on Mathematical and Computer Engineering, ICMCE – 2017, vol. 1. VIT University , 2017.[Abstract]


Unit commitment (UC) problem is an important optimizing task for scheduling the on/off states of generating units in power system operation over a time horizon such that the power generation cost is minimized. Since, increasing the number of generating units makes it difficult to solve in practice, many approaches have been introduced to solve the UC problem. An effort to develop a unit commitment approach capable of handling large power systems consisting of both thermal and hydro generating units offers a large profitable return. In order to be feasible, the method to be developed must be flexible, efficient and reliable. In this paper, various proposed methods have been described along with their strengths and weaknesses. As all of these methods have some sort of weaknesses, a comprehensive algorithm that combines the strengths of different methods and overcomes each other’s weaknesses would be a suitable approach for solving industry-grade unit commitment problem.

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2015

R. Subramani, “Design of an Optimization Model for Power Management Systems”, International Conference on Advances in Mechanical Engineering, vol. 3. Anna University , pp. 1164-1169, 2015.