Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Distributed Optimal Co-multi-microgrids Energy Management for Energy Internet

Unlike conventional power systems, the upcoming energy internet U+0028 EI U+0029 emphasizes comprehensive utilization of energy in the whole power system by coordinating multi-microgrids, which also brings new challenge for the energy management. To address this issue, this paper proposes a novel consensus-based distributed approach based on multi-agent framework to solve the energy management problem of the energy internet, which only requires local information exchange among neighboring agents. Correspondingly, two consensus algorithms are presented, one of which drives the incremental cost of each distributed generator U+0028 DG U+0029 converge to the state of the leader agent-energy router, and the other one is used to estimate the global power mismatch, which is a first-order average consensus algorithm modified by a correction term. In addition, in order to meet the supply-demand balance, an effective control strategy for the energy router is proposed to accurately calculate the power exchange between the microgrid and the main grid. Finally, simulation results within a 7-bus test system are provided to illustrate the effectiveness of the proposed approach. © 2014 Chinese Association of Automation.

Real-Time Energy Management for Net-Zero Power Systems Based on Shared Energy Storage

Battery energy storage systems(BESSs)serve a crucial role in balancing energy fluctuations and reducing carbon emissions in net-zero power systems.However,the efficiency and cost performance have remained significant challenges,which hinders the widespread adoption and development of BESSs.To address these challenges,this paper proposes a real-time energy management scheme that considers the involvement of prosumers to support net-zero power systems.The scheme is based on two shared energy storage models,referred to as energy storage sale model and power line lease model.The energy storage sale model balances real-time power deviations by energy interaction with the goal of minimizing system costs while generating revenue for shared energy storage providers(ESPs).Additionally,power line lease model supports peer-to-peer(P2P)power trading among prosumers through the power lines laid by ESPs to connect each prosumer.This model allows ESP to earn profits from the use of power lines while balancing power deviations and better consuming renewable energy.Experimental results validate the effectiveness of the proposed scheme,ensuring stable power supply for net-zero power systems and providing benefits for both the ESP and prosumers.