Hybrid multi-agent based resilient control for EV connected micro grid system

Abstract

A hybrid control strategy for the energy management of the microgrid system consisting of a number of electric vehicles and other energy sources is proposed in this paper. The main focus of this paper is on optimal control of power flow by scheduling and demand side management of energy generation system and the load by utilizing electric vehicles' energy storage system. The features of a centralized control and distributed control are combined into the proposed hybrid control strategy to improve the efficiency and reliability of the microgrid system consisting of electric vehicle charging stations. Cost of power generation and value of load equations are presented to compute a "situational aware" power balance. Simulated results utilizing these equations are presented for a residential scale proof-ofconcept system.

State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

“…Each agent communicates in its local grid and can also communicates with other agents outside its local neighbourhood. MAS has been used in the literature to model communication in MG control [3,8,54]. Agents' communication can be categorized as P2P or non-P2P [55].…”

“…Non-P2P is synonymous with centralized control, where there is no direct information flow between agents; instead, a central entity exists for information sharing. For example, the model in [54] used a central database as information storage. Each agent acquires information about other agents, as well as updates its own status using the database.…”

Multi-Objective Configuration Optimization for Isolated Microgrid With Shiftable Loads and Mobile Energy Storage

“…This goal, illustrated by equation (19), is to minimize the consumption of nonrenewable energy during the full lifecycle of the designed microgrid; this goal is equivalent to maximizing the proportion of renewable energy in the system's energy supply.…”

“…Recent research on the regulation capacity of mobile energy storage has focused mainly on a microgrid connected to a main grid [17], whereas off-grid system research has been limited. The relevant results have focused mainly on microgrid operation scheduling [18], energy management, and charging pile planning and operation [19], while only a small portion of the literature has considered the impact of mobile energy storage on other energy unit planning, and the energy storage characteristics have usually not been considered in the design process of the operating strategy, which results in the full use of the energy storage being impossible [20] or the optimization being conducted on capacity without operational considerations [21]. In addition, the optimization of the microgrid capacity in the above studies often selects a single economic target [19]; however, the ability to make a comprehensive trade-off is preferred for most users when making decisions, and that makes multiobjective optimization more practical.…”

Robust Hybrid Control for Demand Side Management in Islanded Microgrids

“…However, these references only consider shifting loads or adjusting loads, without dealing with both at the same time. Moreover, in [22], a DR algorithm based on hybrid multi-agent theory for microgrids was presented, but without stability and robustness guaranties.…”