Distributed Agent Consensus-Based Optimal Resource Management for Microgrids

Abstract

Abstract-This paper considers the optimal resource management problem for microgrids. Microgrids provide a promising approach to fulfil challenges of the integration of distributed renewable generations and energy storage systems. However, the resource management in a microgrid encounters the new difficulty, i.e. supply-demand imbalance, caused by the intermittence of renewable sources. Therefore, an optimal solution is proposed to the resource management by enhancing the communication and coordination under a multi-agent system framework. An agent is a participant, for instance, the distributed renewable generator/energy storage system of the microgrid. With this multi-agent system, the distributed optimal solution only utilizes the local information, and interacts with the neighbouring agents. Thus, single-node congestion is avoided since the requirement for a central control centre is eliminated, and it is robust against single-link/node failures. The analysis will show that the proposed solution can solve the resource management problem in an initialization-free manner. Additionally, the proposed strategy can maintain the supply-demand balance under a time-varying supply-demand deviation. The simulation studies are carried out for IEEE 14-bus and 162-bus power systems to validate the effectiveness of the proposed distributed solution.

Consensus-Based Distributed Optimal Energy Management With Less Communication in a Microgrid

“…In the first two cases, the proposed distributed algorithm is tested in a modified IEEE 14-bus system as depicted in Fig. 2, including two CGs, three BESSs and one WT, which is widely adopted in energy management problem [16], [38], [39] . The simulation parameters are summarized in Table. I where the power loss coefficients are adopted in [40], and the topology of the communication network is assumed to be identical to the physical network.…”

Mitigation of distribution system net‐load ramping using multi‐microgrid system

“…The central principles of reliability-centered maintenance and corresponding mathematical concepts for its implementation in MGs are discussed in Moradi et al 6 The uncertainty of intermittent resources as a determinative factor is taken into account in EMS with optimal control of multiple ESS, 7 stochastic programming, 8 Monte Carlo verification, 9 two-stage optimizing (reference/coefficient) method, 10 and single-level mixed-integer linear programming. 11 Zhao and Ding and Zheng et al 12,13 proposed resource management under a multi-agent system framework in which the distributed optimal solution only utilizes the local information, and interacts with the neighboring agents. Also, the optimal management of energy generation/consumption units in the distribution system was formulated in Arefifar et al 14 as multi-microgrid (MMG) system.…”

“…In the first step, the start point could be randomly chosen as decision variables between the lower and upper bound of the capacity of units. Also, the decision variable for the initial state of ESS scheduling is chosen considering (12). Therefore, the solution array for nth neighbor has two sub-structures as shown in (27) and (28) and corresponding costs are given in (29).…”

Novel Distributed Optimal Control of Battery Energy Storage System in an Islanded Microgrid with Fast Frequency Recovery

“…Moreover, the distributed cooperative control strategy proposed in [17] also effectively maintains total power balance and minimizes total power loss. Then, inspired by the dynamic average consensus estimation method, an optimal control strategy is proposed in [18] to minimize the generation cost of components in a distributed manner. With further investigation of the distributed algorithm, authors in [17,18] propose a novel distributed strategy in [13] to coordinate multiple BESSs under wind uncertainties.…”

“…Then, inspired by the dynamic average consensus estimation method, an optimal control strategy is proposed in [18] to minimize the generation cost of components in a distributed manner. With further investigation of the distributed algorithm, authors in [17,18] propose a novel distributed strategy in [13] to coordinate multiple BESSs under wind uncertainties. The fully distributed power dispatch method proposed in [19] achieves rapid frequency recovery and minimizes generation cost for a microgrid, in which a subgradient-based consensus algorithm is used to recover frequency and an average consensus algorithm is used to eliminate frequency disturbance caused by measurement error.…”