Pathirikkat Gopakumar

Smart Fault Location for Smart Grid Operation Using RTUs and Computational Intelligence Techniques

The smart grid aims to improve the quality and reliability of power at the generation, transmission, and distribution levels. The transmission lines can be considered the arteries of the power system, as they carry power over long distances and are exposed to difficult terrain. Transmission line protection philosophy is undergoing a change of paradigm with the advent of digital relays and high-speed broadband communication with the global positioning system (GPS). This paper explores the possibility of transmission line protection for a multigenerator system using wavelet multiresolution analysis (MRA) and computational intelligence techniques in conjunction with GPS. The inputs for the wavelet transform are the synchronized currents measured from remote telemetry units (RTUs) using GPS technology on different buses. The smart location technique uses a wavelet MRA technique to extract the features of the transient current signals based on the harmonics generated at the instant of occurrence of faults due to the abrupt changes of currents in a three-phase transmission line. These extracted features, with such computational intelligence techniques as an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN), lead the grid toward smarter strategies for locating the fault distance. A comparative study establishes the superiority of ANFIS over ANNs for more accurate and reliable smart fault location. Furthermore, the efficacy of the proposed method is validated through a Monte Carlo simulation to incorporate the stochastic (random) nature of fault occurrence in a real-time transmission line. The most significant contribution of this paper is that the proposed smart location technique is immune to the effects of the fault inception angle (FIA), fault impedance, fault distance, and power angle. The results contained in this paper validate the use of the proposed algorithm for the real-time smart grid operation of transmission lines.

Letter to the Editor: Stability Concerns in Smart Grid with Emerging Renewable Energy Technologies

Abstract The environmental concerns due to conventional power plants have given impetus for widespread utilization of renewable energy based distributed generation technologies. As a consequence, the concepts pertaining to a smart grid with advanced functional architecture are evolving to incorporate these technologies. Many such smart grid strategies are focused on maximum utilization of renewable energy sources compared to conventional fossil or nuclear fuels for meeting real-time load demand. The diverse characteristics of renewable energy based distributed generation technologies compared to conventional power plants have led to many operational stability concerns for the smart grid. This article discusses these stability concerns in smart grid with distributed generation technologies.

Fault Detection and Localization Methodology for Self-healing in Smart Power Grids Incorporating Phasor Measurement Units

Abstract Recent developments in several fields of engineering have accelerated the evolution of smart power grids encompassing both transmission and distribution systems across the globe. Self-healing, a crucial operational function of a smart power grid, requires detection as well as localization of the transmission line faults in the power network in real time. A support vector machine based fault-localization methodology has been proposed to accurately detect and localize any type of transmission line faults for the entire smart power grid. This methodology identifies the transmission line fault in smart power grid and precisely pinpoints the bus to which the faulty branch is connected. Afterward, the faulty branch is discriminated, and the distance of fault location from the bus related to the fault is estimated. The methodology relies on frequency-domain analysis of the equivalent voltage phasor angle and equivalent current phasor angle using fast Fourier transform. The proposed methodology has been corroborated using extensive case studies conducted on 7- and 13-bus power systems. The major contribution of the proposed methodology is that it can identify and localize all types of transmission line faults using phasor measurement unit measurements. The methodology can be applied for transmission systems as well as distribution systems.

A Novel Topological Genetic Algorithm-Based Phasor Measurement Unit Placement and Scheduling Methodology for Enhanced State Estimation

Abstract Phasor measurement units are emerging as a potential tool for on-line power system state estimation. Incorporation of phasor measurement units to the existing power systems monitoring system is impeded by various physical and economic constraints. This article proposes a novel topological genetic algorithm for optimal placement of phasor measurement units along with existing conventional measurement units such that state estimation can be achieved with enhanced accuracy and immunity against power grid contingencies. The proposed algorithm optimally places phasor measurement units so that complete observability of the power system is achieved through them and enhanced redundancy in measurement can be accomplished through conventional measurement units. Since practical phasor measurement unit placements are accomplished in multiple horizons, intelligent sorting and phase optimization methodologies have been presented to attain maximum observability during phasing periods. Placement of phasor measurement units with multiple channel limits has also been studied in this article. The efficacy of the proposed topological genetic algorithm for optimizing the number of phasor measurement units and enhancing state estimation under various operating conditions has been validated through extensive simulation studies conducted in IEEE standard bus systems. Practical case studies have been performed in the western and southern region Indian power grids.

Optimal placement of phasor measurement units for Tamil Nadu state of Indian power grid

The growing demand for electricity makes the power grid ever expanding day by day and more and more complex. There is a potential requirement to continuously monitor the power grid and thus making it smarter and reliable. Traditional measurement systems are getting replaced by PMUs, which enables the online monitoring of the power system. With the aid of GPS, PMUs can measure the phasor values of voltages at the bus, where it is placed and the current through the branches connected to that bus. The Current measurement enables us to estimate the voltages at the neighbouring buses. Because of this, placing PMUs at all buses for the complete monitoring of the power system is redundant. Finding the optimal locations of PMUs to make the power system completely observable is of great research interest. This paper proposes the optimal locations of PMU in Tamil Nadu state of Indian power grid using ILP. PMU placement problem has been formulated and optimization has been carried out. Results showing the various optimal locations are tabulated.

A case study on optimal phasor measurement unit placement for emerging Indian national smart grid

India is on the way for transforming its power grid to a modern, intelligent grid called Smart grid. It can transform the Indian power grid to an efficient, reliable, resilient and eco-friendly power system network. The present Indian power grid has to undergo major reformations in wide areas like control methods, communication technologies and monitoring systems to achieve the goal of Indian national smart grid. In this regard, it is essential to incorporate phasor measurement units (PMUs) in power grid monitoring system. The higher financial burden owing to PMU placements across the grid invites the researches for its optimal placement that deliver complete observability of the grid. This paper deliberates optimal locations for PMU placement in Indian power grid for achieving complete observability. Simulated annealing approach is adopted in this paper for optimizing the PMU locations to attain complete observability.

Stability Control of Smart Power Grids with Artificial Intelligence and Wide-area Synchrophasor Measurements

Abstract—Environmental concerns due to emissions from nuclear and fossil fuel based power plants have triggered widespread utilization of renewable energy-based small- and large-scale distributed generation technologies. These technologies have been transforming the energy market towards a deregulated and dispersed entity. To cope with these transformations, and ensure appropriate grid monitoring and control, the conventional power grids across the globe have been enduring a paradigm shift towards a smart grid that is empowered with cutting edge technologies. The operational stability of these emerging smart power grids necessitates sophisticated real-time monitoring and control technologies. This article analyzes various stability concerns in smart power grids pertaining to distributed generations and proposes novel methodologies for ensuring operational stability. The proposed methodologies entail real-time stability monitoring and stability control with the use of wide-area synchrophasor measurements and artificial intelligence methods. The efficacy of the proposed methodologies has been verified through simulation studies conducted on an IEEE 14-bus system. Results of this research validate the necessity of coordinated control for maintaining stability of smart grids incorporating distributed generation technologies.