Optimal Energy Management in Autonomous Power Systems With Probabilistic Security Constraints and Adaptive Frequency Control

Chapaloglou, Spyridon; Alves, Erick Fernando; Trovato, Vincenzo; Tedeschi, Elisabetta

doi:10.1109/tpwrs.2023.3236378

Cited by 7 publications

(1 citation statement)

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“…The need for flexibility in modern power systems has led to the emergence of microgrids (MGs) as a new way to incorporate more interconnected distributed energy resources while meeting both local and larger scale grid objectives. Depending on the application, such structures can be either completely autonomous [1] (isolated) or operate in islanded and/or grid-connected modes [2]. The control of renewable energy resources (RES), energy storage systems (ESS) and electrical loads, all connected to the grid via power electronic devices, is facilitated by the use of MGs [3].…”

Section: Introduction 1background and Motivationmentioning

confidence: 99%

Optimal Generation Capacity Allocation and Droop Control Design for Current Sharing in DC Microgrids

2023

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Considering the increasing amounts of renewable energy generation and energy storage required to meet ambitious environmental goals, it is clear that the next generation of power grids will be dominated by converter-connected devices. In addition, the increasing share of loads connected via power electronics and the general transition to non-synchronous grids with distributed generators make dc microgrids an attractive future alternative. However, achieving optimal utilization of distributed generators in such cases is a complex task, as the performance depends on both the grid and control design. In this paper, we consider such a case where the optimal utilization of distributed generators is achieved by optimal power sharing while taking into account the grid topology, the available generators, and the way they are controlled. For the latter, we consider a droop-based decentralized control scheme whose primary objective is to achieve voltage regulation in the allowable operating range. A novel mixed-integer optimization approach is proposed to identify the optimal converter size and location in the network so that the microgrid can operate safely and with optimal use of the available resources. Time-domain simulations are used to validate the proposed approach and demonstrate its robustness to uncertainty in generator availability.

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Section: Introduction 1background and Motivationmentioning

confidence: 99%