No abstract

The energy market is gradually changing from centralized trading to peer-to-peer trading due to the tremendous increase in a microgrid with green energy resources. When more generating units are included in the microgrid, the possibilities of more reactive power flows exist in the system that leads to high transmission loss which has to be optimized. The reactive power is one of the essential ancillary services in the microgrid towards preserving the voltage in the transmission and distribution line. The major contribution of the paper is towards managing the ancillary service in the distributed energy network economically and technically. This study aims to estimate and optimize the power loss, reactive power, and price management as well. Towards optimization, the self-balanced differential evolution algorithm (SBDE) is used in this study. A distribution system operator is involved in coordinating the sellers and buyers. The proposed layered microgrid architecture uses the blockchain technology for reactive power price management by providing transparency and security among peers. The process of converging various transactions into a block and adding in the distributed blockchain is illustrated. Multiple transactions are performed by using the proposed methodology, giving efficient energy transaction. The results show that the power loss is minimized using SBDE algorithm for different cases. Additionally, the study has demonstrated the price allocation of the optimal reactive power obtained from providers. The blockchain technology embedded in reactive power pricing will play a significant role in the evolution of traditional power distribution systems to active distribution networks.

Stochastic assessment is a method to predict the severity and number of voltage sags at a bus of interest in the transmission network. In this paper, a technique using impedance matrix for stochastic assessment was developed to predict the voltage magnitudes due to faults at any bus in the electrical network. The proposed technique was applied to IEE 24-bus electrical network to illustrate its application. The results show that the proposed technique is able to compute the predicted voltage magnitude at any bus and the number of sags per year.

Stochastic assessment is a method to predict the severity and number of voltage sags at a bus of interest in the transmission network system. In this paper, an analytical technique using impedance matrix is developed to predict the voltage magnitudes due to balanced and unbalanced faults at unlimited buses in an electrical network. The proposed technique was applied to an IEEE 24-buses electrical network to illustrate its application. The results show that the proposed technique is able to predict the voltage magnitude at any buses and the number of sags per year. Keywords-component; Power quality, stochastic methods, voltage sags, balanced and unbalanced fault.I.