Distributed Finite-Time Optimal Resource Management for Microgrids Based on Multi-Agent Framework

Abstract

Abstract-This paper investigates the optimal resource management in a microgrid under various operating conditions. A two-level optimization system is proposed for the distributed optimal resource management based on a multi-agent system framework. The proposed strategy generates a reference of the optimal power output at the top-level through local communication. This strategy only requires the information among neighbouring participants without a central control coordination, and simultaneously accomplishes resource optimization in a finite-time while maintaining the supply-demand balance. The bottom-level control is responsible for the reference tracking of each corresponding participant in a microgrid. The convergent rate of the proposed algorithm is compared with other consensus-based algorithms through simulation studies. Simulation results in the IEEE 14-bus system and an actual islanded system are also presented to demonstrate the overall effectiveness of the proposed strategy.

Distributed voltage and frequency synchronisation control scheme for islanded inverter‐based microgrid

“…To test the scalability, in this case, we analyse the performance of the proposed restoration algorithm for the modified IEEE-39 bus system. It consists of ten DG units and the topology and specifications are provided in [43]. Before t = 2 s only primary droop control was active which results in voltage and frequency deviations.…”

Real‐time stochastic operation strategy of a microgrid using approximate dynamic programming‐based spatiotemporal decomposition approach

“…Apart from ICC-based algorithms, it is reported that distributed gradient-based methods are regarded as another popular category of distributed algorithms for solving ED problem [15][16][17][18]. Moreover, in order to design the decentralised ED algorithm with a fast convergence rate, finite-time consensus algorithms are proposed in [19,20]. However, the aforementioned spatial distributed algorithms [14][15][16][17][18][19][20] are usually applied in the static ED problems of MG, which are limited to the fixed scheduling plan during one period and cannot respond to unexpected variability of RES in a long term [21].…”

“…Moreover, in order to design the decentralised ED algorithm with a fast convergence rate, finite-time consensus algorithms are proposed in [19,20]. However, the aforementioned spatial distributed algorithms [14][15][16][17][18][19][20] are usually applied in the static ED problems of MG, which are limited to the fixed scheduling plan during one period and cannot respond to unexpected variability of RES in a long term [21]. In recent years, the alternating direction method of multipliers (ADMM) algorithm has also been applied to the decentralised optimisation of distribution networks.…”

Event‐triggered distributed optimisation for multi‐agent systems with transmission delay

“…In recent years, distributed optimisation has attracted more and more attention with the development of network technology [1, 2]. It has been widely used in distributed computation [3], sensor network [4, 5], power systems [6, 7] and so on. Compared to traditional optimisation methods, distributed optimisation enables a transition from the centralised framework to the distributed framework.…”