Welcome to our website!
- Our group
research is focussed on finding solutions for intermittent renewable
energy, deregulation, changing energy market, changing control
architecture and electric vehicle integration to grid.
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Frequent metering information will make it possible for the consumer to alter his/her behavior so as to reduce consumption during peak time. We are working on utilizing cloud computing techniques for Demand Response (DR) which will reduce the need for expensive peak generation and expansion of transmission lines. Current cloud computing technology has the potential needed to provide the security, scalability and performance required for near-real time distribution network operation. We have also been working on developing Multi Agent Systems (MAS) based communication and control scheme for pre-dispatch of resources considering the objectives of market players and post-dispatch in real-time to maintain the schedules and respond to price changes. A coordinated control scheme is being developed with restoration and volt/var control that can enhance the reliability and efficiency of system operation.
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The technological breakthroughs made by the availability of low cost metering, low-cost, low-power computing devices, high speed communications, larger storage spaces, greater internet bandwidths has led to increased attentions towards the advantages of these systems bringing forth physical operation controlled and integrated by communications and computing. These breakthroughs are creating yet another challenge for power systems operations with the meters presenting an increased dependency on cyber assets making them prone to attack. We are trying to identify and solve fundamental research challenges needed to transform cybersecurity of grid cyber physical systems to reality by developing Real Time Attack Management and Control (RAMC). We are also exploiting new ideas for scaling databases and algorithms also readying them for parallelizing.
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As part of Grid Technologies Collaborative project with NETL and five other universities we are involved in developing coordinated control for renewable sources. As part of NSF grant we are also developing dynamic models and decentralized control strategy for electric vehicles that operate in grid connected mode and transportation mode fulfilling demands. In the military context, typical control applications are optimal pursuit and mobile shape formations. A major roadblock to improve sensor-network control is the tradeoff between communications, energy efficiency, and missing information recovery using existing algorithms. Despite reliable mechanisms for state estimation, data can be expected to be delayed or lost in a sensor network. Motivated by these fundamental problems we are developing, a multi-agent based decentralized algorithm which has potentials to control wireless sensor network for real-time control applications.
Contact Information
Email: jmsolanki@csee.wvu.eduOffice: AERB 239
Office Phone: 304.293.5071
Lab: ERB 219
Sponsors
