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Shailesh Wasti

Publications and source records attributed to Shailesh Wasti.

3 recordsLinked to original sources

An ADMM-based MIQP platform for the EV aggregation management

Electric vehicle (EV) aggregation can significantly influence the EVs charging/discharging behavior. In this paper, we use a distributed algorithm based on the alternating direction method of multipliers (ADMM) to coordinate EV charging and discharging procedures for EVs with vehicle-to-grid (V2G) capabilities. The optimization model is formulated as a mixed-integer quadratic programming (MIQP) problem to consider the efficiency of EV batteries and different energy prices in both charging and discharging processes. Numerical tests using real-world data confirms that the implemented method allows obtaining both the electric vehicle aggregator (EVA) and individual EV goals while considering the power grid and each EV constraints. Moreover, we show the significant impact of our model on the final demand profile and computation time.

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Distributed Dynamic Economic Dispatch using Alternating Direction Method of Multipliers

With the proliferation of distributed energy resources and the volume of data stored due to advancement in metering infrastructure, energy management in power system operation needs distributed computing. In this paper, we propose a fully distributed Alternating Direction Method of Multipliers (ADMM) algorithm to solve the distributed economic dispatch (ED) problem, where the optimization problem is fully decomposed between participating agents. In our proposed framework, each agent estimates the dual variable and the average of the total power mismatch of the network using dynamic average consensus, which replaces the dual updater in the traditional ADMM with a distributed alternative. Unlike other distributed ADMM, the proposed method does not rely on any specific assumption and captures the real-time demand change. The algorithm is validated successfully via case studies for IEEE 30-bus and 300-bus test systems with the penetration of solar photovoltaic.

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MMC-Based Distributed Maximum Power Point Tracking for Photovoltaic Systems

This paper proposes a novel topology for grid connected photovoltaic (PV) system based on modular multilevel converter (MMC). In this topology, a PV array is connected to capacitors of each submodule (SM) of the MMC through a DC-DC boost converter with maximum power point tracking (MPPT) control. This topology will maximize the efficiency of the system in the case of partial shading conditions, as it can regulate the SM capacitor voltages independently from each other to realize distributed MPPT. A model predictive control is used to track the AC output current, balance the SMs capacitor voltages, and to mitigate the circulating current. The proposed PV generation topology with 7 level MMC system validity has been verified by simulations via MATLAB/Simulink toolbox under normal operation, partial shading and PV array failure.

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