BOKKISAM HANUMANTHA RAO
@nitrkl.ac.in
Assistant Professor
NIT Rourkela, India
Dr. Hanumantha Rao Bokkisam is currently an Assistant Professor in the Electrical Engineering Department at the National Institute of Technology Rourkela (NITRKL), India, where he is associated with the Power System group. He is a member of the IEEE. Previously, he worked as a Senior Power System Researcher at the School of Electrical and Electronics Engineering, University College Dublin, Ireland. His research focuses on "Blockchain transactions in the electricity industry: beyond tokenized energy," which is a collaborative project between University College Dublin (UCD), Ireland, and the University of Edinburgh, UK. His research at UCD was financially funded by the Science Foundation of Ireland (SFI), Government of Ireland. Dr. Bokkisam holds a Ph.D. degree from the National Institute of Technology, Tiruchirappalli (NITT), where he conducted research on "Investigation of transactive energy market frameworks for community microgrids with demand response and peer-to-peer energy trading
EDUCATION
PhD in Electrical Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Energy, Energy Engineering and Power Technology
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Nareddy Nageswara Reddy, Hanumantha Rao Bokkisam, Ravi Kumar Avvari, and Anil Kumar Annamraju
IEEE
In ring configuration microgrid, the distributed energy sources installed at different locations of the network. It offers bi-directional power flow rarer than unidirectional power flow. During faulty conditions, it may leads to an unwanted disconnection of sources and makes the system is unstable. To overcome the lack of selectivity, sensitivity and for better reliability of the DC microgrid (DCMG), a quick and precise protection strategy need to be required. Moreover, due to improper discrimination of fault from sudden load changes the protection devices may subject to mal - operation and results in discontinuity of power to consumers. This article presents a precise protection strategy for fault isolation and detection in DCMG. Initially, the disturbance in the system detects with the help of difference in current value. Subsequently, the proper discrimination of fault inception and sudden changes in load has been carried out using the second order derivatives. Further, an inductance method evaluated for an isolation of the fault section. The genuineness of the proposed method is validated for various cases like low and high resistance faults, fault at different locations of line in MATLAB/Simulink. And also, this method has been investigated for different load conditions. Comparative assessment has been done with available protection methods and proved that the proposed method found to be more accurate.
Iacopo Savelli, Hanumantha Rao Bokkisam, Paul Cuffe, and Thomas Morstyn
Elsevier BV
Bryan Bird, Hanumantha Rao Bokkisam, Iacopo Savelli, Thomas Morstyn, and Paul Cuffe
IEEE
The rapid onboarding of renewable generation has led to many difficulties for both generators and the grid due to volatile output and market conditions. Battery energy storage systems have begun to alleviate these issues. However, such systems face many financial challenges in their deployment and operation. This paper demonstrates the use of advanced distributed ledger technology with smart contracts to design a decentralised autonomous organisation (DAO) to manage the investments in these systems and optimise their operations. In this paper, a series of smart contracts have been designed, deployed, and tested to demonstrate the effectiveness of such a DAO framework for battery management. The interconnected smart contracts can manage the financing, governing, and revenue-sharing mechanisms, allowing investors to coordinate investment and vote on the battery energy storage system's operation (charge/float/discharge) for a given period. This interconnected smart contract design implementation demonstrates a novel and effective strategy for managing battery energy storage systems, decreasing barriers to entry for investors, thus, allowing a greater adoption of such technology.
Hanumantha Rao Bokkisam, Ritesh Mohan Acharya, and Selvan M.P.
Elsevier BV
Hanumantha Rao Bokkisam, Iacopo Savelli, Thomas Morstyn, and Paul Cuffe
IEEE
This paper presents a framework for a blockchain-based decentralised autonomous organisation that mediates the financing, governance, and revenue dispersal for a battery energy storage system fully controlled by remote token holders. In the proposed framework, the participants can buy a fractional share of an energy storage asset, embodied as a blockchain token, with corresponding rights and privileges enforced by smart contracts. The token holders continually vote to govern the battery’s operation (charge/float/discharge); these votes are autonomously aggregated by the smart contract, which is also empowered to directly dispatch the battery’s mode of operation by issuing physical control signals. Furthermore, the smart contract itself maintains a financial payment channel with the electricity market, transacting stable coins back and forth as it buys and sells energy from the spot market, per the token holders’ consensus wishes. This paper presents a case study simulation of this radical conception of asset ownership and control, whereby token holders vote based on the real-time price of electricity, their particular electricity price forecast, and the current state of charge of the battery.
Ritesh Mohan Acharya, Bokkisam Hanumantha Rao, and Manickavasagam Parvathy Selvan
Hindawi Limited
Hanumantha Rao Bokkisam and Selvan M.P.
Elsevier BV
Bokkisam Hanumantha Rao and Selvan M. P
IEEE
This paper presents a framework of transactive energy marketplace (TEM) in a community microgrid with multiple prosumers as market participants for facilitating peer-to-peer (P2P) energy trading with demand response consideration. The internal market prices are determined using generation-to-demand ratio with the help of transactive energy market operator (TEMO). The TEMO is a non-profited retail energy manager that aims to enable prosumers to participate in the TEM, and to sustain equilibrium between community generation and demand. The participants in TEM are encouraged to trade their net demand with the neighborhood besides the upstream utility. The interactions between TEMO and prosumers are modeled with the game-theory. The optimal time slots for the schedulable loads of the prosumers in TEM are obtained using genetic algorithm while optimizing the energy bills. With the presented system, the reduction in the community energy bills is in the range of 18-52% in the P2P marketplace compared to conventional peer-to-grid (P2G) marketplace under different scenarios.
Bokkisam Hanumantha Rao, Saravana Loganathan Arun, and Manickavasagam Parvathy Selvan
Institution of Engineering and Technology (IET)
This paper proposes an architecture of locality electricity market (LEM) for peer-to-peer (P2P) energy trading among a group of residential prosumers (consumers and producers) with renewable energy resources, smart meters, information and communication technologies, and home energy management systems in a smart residential locality. Prosumers may sell(buy) their excess generation(demand) in LEM at a profitable prices compared to the utility prices in P2P fashion. In order to manage the trading in LEM, a common portal named as locality electricity trading system (LETS) is introduced. The purpose of LETS is to prepare a trading agreement between the participants by fixing a price for every deal based on the quoted price and day-ahead power trading schedule given by the participants. An enhanced intelligent residential energy management system (EIREMS) is proposed at the prosumers' premises to enable their participation in the day-ahead energy trading process and in real-time scheduling of schedulable loads and battery for reducing the electricity bill with due consideration to the operational constraints and LETS agreement. The performances of proposed LETS and EIREMS are validated through a few case studies on a locality with ten prosumers. The proposed methodology endorses marginal economic benefit for all the participants.
K Navya Krishnan, B. Hanumantha Rao, S.L Arun, and M.P. Selvan
IEEE
Demand response programs in smart grid environment encourage the energy consumer to interact directly with the grid so that they can participate in electricity market actively. In this paper, a locality in smart power system is considered, where each consumer is intending to reduce the energy consumption cost by jointly scheduling their electric appliances. Non-cooperative game theory is applied to frame the distributed load scheduling game, where the consumers are considered as the players and the energy consumption schedules of their appliances as strategies. Genetic Algorithm (GA) is used as the optimization tool for individual consumer load scheduling to minimize the electricity bill. Interactive scheduling is done using both simultaneous method and sequential method.