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Author

K. Shanti Swarup

Bio: K. Shanti Swarup is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Smart grid & Relay. The author has an hindex of 13, co-authored 77 publications receiving 677 citations.


Papers
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Book ChapterDOI
06 Jul 2015
TL;DR: Different energy consumption scheduling techniques that schedule the house hold appliances in real-time to achieve minimum energy consumption cost and to reducepeak load demand in peak hours to shape the peak load demand are observed.
Abstract: In recent years the load demand by residential consumers are rapidly increasing due to the usage of many electric appliances in daily needs. Load demand during peak hours is becoming increasingly larger than off-peak hours, which is the major reason for inefficiency in generation capacity. Introduction of smart grid technology in Demand Side Management programs provides an alternative to installation of new generation units. Consumers can play a major role in reducing their energy consumption by communicating with utilities so that they can minimize their energy costs and get incentives, which also helps utilities in many ways. Smart grid technologies provide opportunities to employ different pricing schemes which also help in increasing the efficiency of appliance scheduling techniques. Optimal energy consumption scheduling reduces the peak load demand in peak hour. Peak average ratio (PAR) also minimizes the energy consumption cost. In this paper, we observes different energy consumption scheduling techniques that schedule the house hold appliances in real-time to achieve minimum energy consumption cost and to reduce peak load demand in peak hours to shape the peak load demand. Formulation and Solution methodology of residential energy consumption scheduling is presented with simulation results illustrating the working of the model.

1 citations

Journal ArticleDOI
TL;DR: In this article, a new technique for selection of participating generators and load buses using direct acyclic graph (DAG) is presented, which is computationally fast, reliable and efficient in restoring the system to normal state after a contingency with minimal control actions.
Abstract: Transmission line overload initiate the cascading outages, which forces the system to collapse. The most practiced techniques for overload alleviation is generator rescheduling and/or load shedding. The appropriate selection of generators and load buses to perform the control action for overload alleviation is an important task for the operators. Local optimisation based overload alleviation requires appropriate selection of generator and load buses for minimum control action. This paper presents a new technique for selection of participating generators and load buses using direct acyclic graph (DAG). PSO solved the generator rescheduling and/or load shedding optimisation problem with in security constraints. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and 57 bus systems. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions.

1 citations

Proceedings ArticleDOI
01 Dec 2018
TL;DR: An intelligent charging strategy for Plug-in Electric Vehicle (PEV) incorporating a unified grid-to-vehicle(G2V) and vehicle- to-grid(V2G) framework with users' priority is proposed for optimal integration of PEVs in the existing distribution system.
Abstract: The electrification of transport is seen as one of the main pathways to achieve significant reductions in CO2 emissions. However, there are some issues related to it like, a sudden increase in electricity demand, high charging cost in dynamic price market, attending user's priority in charging his/her vehicle and the premium to be levied for such priority. In this paper, an intelligent charging strategy for Plug-in Electric Vehicle(PEV) incorporating a unified grid-to-vehicle(G2V) and vehicle-to-grid(V2G) framework with users' priority is proposed for optimal integration of PEVs in the existing distribution system. The intelligent strategy with objective function considering minimization of total charging cost, with users' priority as well as without priority is developed to study the impact of PEV integration from economic and technical perspective. The proposed strategy is implemented on test bench case consisting of 5 similar PEVs in a parking station. The uncertain parameters like PEV availability at charging station are handled using Monte-Carlo simulation. The bi-linear constraints are modified to pose the problem as a linear optimization problem. A comparative analysis is done on the charging cost with priority and without priority to investigate the economic impact of introducing users' priority. Finally, an investigative study is conducted to assign economic value to priority so the premium can be charged to users for assigning priority to their vehicles. The simulation results present a comprehensive evaluation of the proposed strategy.

1 citations

Proceedings ArticleDOI
01 Nov 2017
TL;DR: The proposed interface protection relay algorithm uses instantaneous symmetrical voltage components for fault detection and the effectiveness of proposed relay algorithm is evaluated by conducting simulation studies using PSCAD/EMTDC software.
Abstract: Large scale integration of distributed generating sources challenges the conventional protection schemes in the distribution networks. The response of inverter interfaced sources to network faults are different from the conventional generators and hence need special protection systems. A new protection methodology for distribution networks with inverter based sources is discussed in the present work. The proposed interface protection relay algorithm uses instantaneous symmetrical voltage components for fault detection. The effectiveness of proposed relay algorithm is evaluated by conducting simulation studies using PSCAD/EMTDC software.

1 citations

Proceedings ArticleDOI
01 Nov 2015
TL;DR: In this paper, a doubly fed induction generator performance optimization using electromagnetic transient simulation (EMTP) program is presented, where the objective function (OF) is formed in terms of design parameters like kp and k of the controller to reduce the error arise due to overshoot, steady state error etc.
Abstract: This paper presents a new method for doubly fed induction generator performance optimization using electromagnetic transient simulation (EMTP) program. A 2 MW doubly fed induction generator(DFIG) is modeled in electromagnetic transient simulation PSCAD/EMTDC. To optimize the performance of DFIG, each controller parameters like kp and k should be properly tuned and cordinated. The objective function (OF) is formed in terms of design parameters like kp and k of the controller to reduce the error arise due to overshoot, steady state error etc. The nonlinear optimization program evaluates the parameter values to minimize the OF value in successive iterations. In this paper, the OF is formed to minimize the error in outer speed control loop of rotor side converter of DFIG.

1 citations


Cited by
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01 Jan 2011
TL;DR: The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h, where the results indicate that for forecasts up to 2 h ahead the most important input is the available observations ofSolar power, while for longer horizons NWPs are theMost important input.
Abstract: This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model.

585 citations

Journal ArticleDOI
TL;DR: The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages ofPSO, the basic variant of PS o, Modification of PSo and applications that have implemented using PSO.
Abstract: Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to process static, simple optimization problem. Modification PSO is developed for solving the basic PSO problem. The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages of PSO, the basic variant of PSO, Modification of PSO and applications that have implemented using PSO. The application can show which one the modified or variant PSO that haven’t been made and which one the modified or variant PSO that will be developed.

395 citations

Journal ArticleDOI
TL;DR: In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360MW pump, 300MW turbine, and a 2GWh storage utilising price arbitrage on 13 electricity spot markets.

245 citations

Journal ArticleDOI
TL;DR: This bibliography will aid academic researchers and practicing engineers in adopting appropriate topics and will stimulate utilities toward development and implementation of software packages.
Abstract: Phasor measurement units (PMUs) are rapidly being deployed in electric power networks across the globe. Wide-area measurement system (WAMS), which builds upon PMUs and fast communication links, is consequently emerging as an advanced monitoring and control infrastructure. Rapid adaptation of such devices and technologies has led the researchers to investigate multitude of challenges and pursue opportunities in synchrophasor measurement technology, PMU structural design, PMU placement, miscellaneous applications of PMU from local perspectives, and various WAMS functionalities from the system perspective. Relevant research articles appeared in the IEEE and IET publications from 1983 through 2014 are rigorously surveyed in this paper to represent a panorama of research progress lines. This bibliography will aid academic researchers and practicing engineers in adopting appropriate topics and will stimulate utilities toward development and implementation of software packages.

239 citations

Journal ArticleDOI
TL;DR: In this article, an energy management system (EMS) based on mixed-integer nonlinear programming (MINLP) is presented for MG in islanding mode considering different scenarios, and a local energy market (LEM) is also proposed with in this EMS to obtain the cheapest price, maximizing the utilization of distributed energy resources.

221 citations