https://research.ece.ncsu.edu/netwis/papers/13wl-comnet.pdf

Survey Cyber security in the Smart Grid: Survey and challenges

Survey Paper: A survey on the communication architectures in smart grid

Islanding detection of distributed generations (DGs) is one of the most important aspects of interconnecting DGs to the distribution system. Islanding detection techniques can generally be classified as remote methods, which are associated with islanding detection on the utility sides, and local methods, which are associated with islanding detection on the DG side. This paper presents a survey of various islanding detection techniques and their advantages and disadvantages. The paper focused on islanding detection using a conventional and intelligent technique. A summary table that compares and contrasts the existing methods is also presented.

A review of islanding detection techniques for renewable distributed generation systems

An elliptic curve cryptography based lightweight authentication scheme for smart grid communication

High impedance fault detection: A review

Home energy management system (HEMS) came out as an important tool for enhancing residential customer demand response applications in smart grid. This paper proposes an efficient algorithm for HEMS which considers customer load priorities and preferences and maintains the power consumption below the sanctioned limit such that minimum comfort violation occurs. The application of proposed algorithm is done for demand response of the selected loads for Indian residential customers. Demand response of the selected appliances based on different utility signal, comfort level status and the loads priority is also analysed for different cases. The paper also discusses hardware design for efficacious handling of household appliances.

An efficient home energy management algorithm for demand response analysis in Indian scenario

Performance of Advanced Metering Infrastructure (Ai€ MI) is improving due to the introduction of International Electrotechnical Commission's (IEC) 61850 standard based smart meters and Intelligent Electronic Devices (IEDs)Â  Whereas, legacy metering infrastructure and devices can not be ignored due to their wide spread use and substantial capital investment, but at the same time advance technology based smart meters are forcing utilities to adopt new technology in meteringÂ  Middle path, before complete transformation takes place, seems to be to make legacy and AMI interoperable This paper proposes a solution where applications from different manufacturers can access a standard interoperable metered data A novel solution is also provided for accessing the meter metadata without manually inputting the address parameters of a particular meter to reduce the development time involved in deploying the AMI head-ends Keywords : AMI, AMI Head-end, IEC 61850, Interoperability, Metadata, Smart Grid, XML Database

/pdf/interoperability-framework-for-data-exchange-between-legacy-5gns7vmm9e.pdf

Interoperability Framework for Data Exchange between Legacy and Advanced Metering Infrastructure

Wide area monitoring system (WAMS) recognizes the condition, quality and stability of various parts of the power transmission network with the help of advent monitoring and measuring equipment. Phasor measurement units (PMUs) have emerged as vital devices for wide-area monitoring systems. Now a day, the optimal placement of PMUs for maintaining the observability of the whole network and providing adequate and reliable communication between them are challenging problems. A novel algorithm is proposed in this paper to identify optimal placement of PMUs by performing observability analysis with reduction in computational burden. This paper includes the optimal PMU placement algorithm and the degree of observability of each bus according to the PMU locations and its applications on IEEE 14 bus system. The simulation work has been performed on Orissa power grid network to show the effectiveness of the proposed methodology.

Optimization of PMU placement by performing observability analysis

Risk-Calibrated conventional-renewable generation mix using master-slave portfolio approach guided by flexible investor preferencing

The use of electric vehicles (EVs) has recently increased in a smart city environment. With this, the optimal location of the charging station is a great challenge and, hence, the energy efficiency performance (EEP) of an electrical system is important. Ideally, the EEP is realized through passive energy boosters (PEBs) and active energy boosters (AEBs). PEBs require no external resources, and EEP is achieved through altering the network topology and loading patterns, whereas, in AEBs, integrating external energy resources is a must. The EEP has also become dynamic with the integration of an energy storage system (ESS) in a deregulated environment. Customer energy requirement varies daily, weekly, and seasonally. In this scenario, the frequent change in network topology requires modifying the size and location of AEBs. It alters the customers’ voltage profile, loadability margin, and supply reliability when the EV works differently as a load or source. Therefore, a comprehensive EEP analysis with different probabilistic loading patterns, including ESS, must be performed at the planning stage. This work uses a harmony search algorithm to evaluate EEP for AEBs and PEBs, in coordination, when ESS works as a load or source, at four locations, for customers’ and utilities’ benefits.

/pdf/impact-of-electric-vehicles-on-energy-efficiency-with-energy-2w79zqk1.pdf

Mini S. Thomas

Papers

An efficient home energy management algorithm for demand response analysis in Indian scenario

Interoperability Framework for Data Exchange between Legacy and Advanced Metering Infrastructure

Optimization of PMU placement by performing observability analysis

Risk-Calibrated conventional-renewable generation mix using master-slave portfolio approach guided by flexible investor preferencing

Impact of Electric Vehicles on Energy Efficiency with Energy Boosters in Coordination for Sustainable Energy in Smart Cities