Decentralized Coordination of Microgrids With Flexible Demand and Energy Storage

Abstract

Scalability and privacy concerns have created significant interest in decentralized coordination of distributed energy resources (DERs) within microgrids. Previously proposed approaches, however, fail to achieve feasible solutions under flexible demand (FD) and energy storage (ES) participation. After justifying and demonstrating this challenge, this paper develops a novel Lagrangian relaxation-based mechanism achieving feasible, nearoptimal solutions in a decentralized fashion, considering both active and reactive power. A two-level iterative algorithm eliminates the infeasibility effect of FD and ES nonstrict convexities, and prevents the creation of new demand peaks and troughs by the concentration of their response at the same low-and high-priced periods. Tradeoffs associated with the design and operation of the mechanism are analyzed, and the value of additional information submission by the DER, in enabling the quantification of an optimality bound of the determined solutions and significant improvements in communication requirements, is assessed. These contributions are supported by case studies on an LV microgrid test system.

Nonlinear and Randomized Pricing for Distributed Management of Flexible Loads

“…This infeasibility co mplication is resolved in [10] by fixing the price responses of such non strictly convex DER for part of the coordination process, where iterations are carried out with the strictly convex DER only. However, the same paper has also demonstrated that an optimality challenge emerges.…”

“…In order to address this challenge, the authors proposed the perturbation of the flexible loads' response through a relative flexibility restriction. In [10] where flexible loads with continuously adjustable power levels are considered, this flexib ility restriction is formed as a maximu m power demand limit. In [11], the authors propose a flexibility restriction for flexible loads whose operating constraints do not allow the continuous adjustment of their power demand levels but the deferral of their fixed operation cycles, in the form of a maximu m cycle delay limit.…”

“…Beyond tackling the above acceptability and feasibility challenges, this non-linear pricing approach is demonstrated to outperform the flexibility restriction approach of [10] in flattening the total demand profile and thus producing high quality solutions, for both types of loads. For deferrable cycle loads, it is shown that employ ment of uniform flexibility restrictions or non-linear prices is not sufficient in achieving efficient solutions, especially if the operating diversity of these loads is low.…”

“…Section II outlines the distributed microgrid management mechanism developed in [10]. Section III formu lates the price response sub-problems of the two examined flexible demand technologies.…”

“…Th is problem is subject to the nodal active (2) and reactive (3) power balance constraints, the voltage (4) and thermal (5)- (6) limits of the distribution network, and the indiv idual operational constraints of the DER (7). As in [10], the responsible entity for microgrid management is termed microgrid market operator (MGM O).…”