Vasudev Dehalwar

Multi-agent based public key infrastructure for smart grid

The electric power grid has been developed over last century and it is facing many problems. The electric grid lacks the ability to adapt and integrate intermittent energy sources and active customer participation. Numbers of architecture have been proposed by various agencies for smart grid. Micro-grid is the lowest node in the hierarchy of smart grid that has to be developed efficiently for optimal performance. Smart grid, which will involve multidirectional energy and information flows, may be susceptible to cyber attack due to involvement of ICT in managing the smart grid. Multiagent based public key infrastructure (PKI) is proposed for the authentication of participating devises in micro-grid. The agents utilize information exchanges from neighboring agents to construct knowledge base that can be used in making efficient decision support system. The studies suggest that multi-agent perform better under the given circumstance and pressure providing the real-time communication.

Data Communication Security of Advanced Metering Infrastructure in Smart Grid

Advanced Metering Infrastructure (AMI) is very critical part for wired/wireless communication in Smart Grid. It involves communication of vital smart metering data to central control center for smooth functioning of smart grid. Security and reliability of data is of paramount importance for operational reliability of smart grid. AMI network is susceptible to many cyber security threats and attacks. Therefore it is desirable to prevent the data from such vulnerabilities. The paper proposes two-phase method to provide security of data using dedicated authentication server which inhibits malicious and unauthorized nodes to gain access to AMI communication network. Secure environment is created by this method that helps in achieving better throughput and packet delivery ratio. Thus, it improves the security and performance of the network.

Infrastructure for real-time communication in smart grid

The existing electricity grid is subjected to numerous challenges that are expected to be overcome by Smart Grid. It is expected to provide utility companies with better visibility and pervasive control over their assets and services. There is no full-proof technology that can provide real-time communication in Smart Grid. This paper explores the possible infrastructure for real-time communication in Smart Grid with modern techniques. Reliable communication can be maintained with better Quality of services. The paper also proposes the innovative algorithm to decongest the network for optimum bandwidth utilization. It is possible to have real-time communication of Big data in Smart Grid through right messages priority and better bandwidth utilization technique of Cognitive Radio.

Review of machine to machine communication in smart grid

Machine to machine communication (M2M) is a communication architecture that enables heterogeneous devices to interact with each other without human intervention. Smart Grid (SG) is one of the many applications areas in the M2M communication. Smart Grid demands advanced communication infrastructure for two-way communications between devices deployed at various locations in energy generation, transmission, distribution and consumption. The billions of electronic devices connected to the Smart Grid pose a big challenge to grid communication. Therefore, a feasible solution to efficient M2M has to overcome challenges of energy efficiency of connected devices, interoperability, coverage area, interference, sleep/wake up time of devices, etc. This paper reviews the current research status in M2M communication, especially for Smart Grid. It also discusses the development of standards for M2M communication. Suitability of Cognitive Radio for Big Data communication in M2M communication network is also examined.

Electricity load forecasting for Urban area using weather forecast information

The global demand for energy is increasing daily with the expansion of energy infrastructure and the addition of new appliances. Efficient Energy Management System (EMS) is the need of the day. All residential and commercial buildings can achieve better energy efficiency and consumption with the use of EMS. Load forecasting is one of the methods to enable EMS to work efficiently. The accuracy of load forecast depends on many factors. The load forecast model must consider the weather forecast for the region in developing an accurate forecast. This paper develops Artificial Neural Network (ANN) and Bagged Regression Trees to generate and predicted load forecast in Urban area using Meteorological data. ANN model is compared with Bagged Regression Trees for prediction accuracy. Good agreement was observed by comparing these results with those available in the literature. It has been observed through analysis that Bagged Regression Trees produce better load prediction for the day ahead load in the urban area.

Integration of IEC 61850 MMS and IEEE 802.22 for Smart Grid Communication

The reliability of Smart Grid depends on two-way communication between substation and utility. IEC 61850 is an international standard defined to ensure interoperability between Substation Automation System (SAS). IEC 61850 services are mapped on the Manufacturing Message Specification (MMS) especially for meter data management system. MMS is the OSI protocol that run over TCP/IP or OSI networks to support IEC 61850 services. Presently, the MMS uses Ethernet as the layer 2 protocol. However, for long distance communication in remote areas wireless communication is the prefered mode. The Cognitive Radio based IEEE 802.22 is next generation standard for Wireless Regional Area Network (WRAN) that can support long distance wireless communication for low-latency, high-volume, reliable and secure communication. This paper shows the potential to integrate IEC 61850 MMS with IEEE 802.22 for long distance Smart Grid communication.

Compliance of IEEE 802.22 WRAN for field area network in smart grid

Distributed power system network is going to be complex, and it will require high-speed, reliable and secure communication systems for managing intermittent generation with coordination of centralised power generation, including load control. Cognitive Radio (CR) is highly favourable for providing communications in Smart Grid by using spectrum resources opportunistically. The IEEE 802.22 Wireless Regional Area Network (WRAN) having the capabilities of CR use vacant channels opportunistically in the frequency range of 54 MHz to 862 MHz occupied by TV band. A comprehensive review of using IEEE 802.22 for Field Area Network in power system network using spectrum sensing (CR based communication) is provided in this paper. The spectrum sensing technique(s) at Base Station (BS) and Customer Premises Equipment (CPE) for detecting the presence of incumbent in order to mitigate interferences is also studied. The availability of backup and candidate channels are updated during “Quite Period” for further use (spectrum switching and management) with geolocation capabilities. The use of IEEE 802.22 for (a) radio-scene analysis, (b) channel identification, and (c) dynamic spectrum management are examined for applications in power management.