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Bi-directional information and energy flow, renewable energy sources, battery energy storage, electric vehicle, self-healing capability, and demand response programs, etc., revolutionized the traditional distribution network into the smart distribution network. Adoption of modern technologies like intelligent meters such as advanced metering infrastructure & Micro-phasor measurement units, data storage, and analysis techniques and incentive-based electricity trading mechanisms can bring this paradigm shift. This study presents an overview of popular technologies that facilitate this transformation, giving focus on some prime technologies such as real-time monitoring based on Micro-phasor measurement units, data storage and analytics, blockchain technology, multi-agent systems, and incentive-based energy trading mechanisms

This paper combines evolutionary game theory and Agent-based modelling for finding out the optimal location and size of multiple solar PVs in an unbalanced distribution system. The use of Agent-based modelling in solar PV placement is new and hence provides a valuable contribution. NashDE algorithm is implemented and simulated using an agent-based modelling framework MESA. In MA-NashDE, the optimization variables, i.e., the power system buses, are clustered into several zones using both the Loss Sensitivity Index and the Voltage Sensitivity Index. Each zone is under the control of a Nash/zonal player, and the strategy adopted by the zonal player will evolve through Multi-Agent Differential Evolution (MADE) algorithm. This is a novel study focusing on the PV placement problem by Agent-based Evolutionary Game Theory. The proposed methodology was tested using IEEE 34 and IEEE 123 bus radial distribution network using the OpenDSS-Python COM interface.

An interconnection scheme and maximum power point tracking algorithm for the current source converter (CSC) based offshore wind farm is presented in this paper. A fault mitigation strategy by utilizing the short circuit operating capability of CSC is also presented. Tip speed ratio control with speed control is used as MPPT technique. A three phase to ground fault, double line to ground fault and single line to ground fault are created very near to the grid connection point. The system is simulated using MATLAB/Simpower system toolbox with an inertia constant of 1s. It is found that the proposed fault mitigation strategy is more faster compared to other existing technique.

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High proliferation of DERs in the distribution system necessitates forecasting ability for state estimator. A dynamic state estimation is a fundamental tool for realizing distribution system automation. Selection of appropriate methodological framework is an essential step before implementing dynamic state estimation. We applied Vector Error Correction Model (VECM), Random Forest and Long Short Term Memory Network (LSTM) time series models to dynamic power system state estimation problem and found out that the LSTM model outperforms the other two in prediction accuracy.

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