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• A discrete prescribed time consensus for robust convergence time control. • An optimal leaders selection scheme to tackle leader corruption issues. • An event triggered communication protocol in battery communication networks. Small scale energy storage systems (ESSs) can serve as buffers for integrating renewable energy resources into the main grid. Their available energy can be aggregated to provide ancillary services for power systems. This paper considers a load frequency control (LFC) scheme with energy storage aggregator comprises of ESSs. To coordinate the behaviors of ESSs for LFC support, a discrete prescribed time consensus control is proposed which ensures that the ESSs can reach consensus within the prescribed settling time. To improve the tracking precision, an optimal leader set is selected with submodular optimization. In the meantime, an event triggered communication (ETC) protocol is proposed to reduce the unnecessary information sharing among ESSs. The ETC protocol is naturally Zeno free with the defined sampling instants. Case studies are conducted to validate the effectiveness of the proposed method, and the performance of the proposed method is superior than conventional and state-of-art methods with comparative studies. [ABSTRACT FROM AUTHOR]

• A multi-objective renewable energy management scheme is proposed. • Cost saving, green consumption and power quality are the main motivations. • A novel multi-agent system with three electricity use mode is developed. • Key implications and recommendations for policy makers are given. This paper proposes a multi-objective renewable energy management scheme to satisfy the needs of diversified community power consumers, wherein the multi-agent system is employed for coordinating and controlling the power generation and consumption units. Firstly, a multi-agent based microgrid and home energy management system is constructed. Subsequently, system models for renewable energy sources, electrical vehicles, residential loads and the cost function are constructed to form the microgrid operation constraints. With these constraints, three optimization models are proposed to minimize the electricity bills, the power purchased from the main grid, and optimize the power quality. The three objectives are proposed to reflect the power consumer's needs for cost saving, green consumption, and power reliability, respectively. Meanwhile, a coordination strategy which balances the three objectives is proposed. After that, a novel multi agent system is proposed to realize the proposed objectives. Four case studies and a sensitivity analysis are conducted to verify the effectiveness of the proposed method. The case study results show that: in electricity minimization, 2–6.5% of total electricity bills can be saved; in main grid power consumption minimization, the peaks of the power consumption profiles are shaved while the valleys of the profiles are filled; in power quality enhancement, the steady state frequency drop is reduced for 0.35 Hz to 0.38 Hz. The sensitivity analysis shows that communities equipped with energy storage systems accounting for 30% of the total load can achieve best optimization outcomes; the increase in renewable energy usage will lead to higher electricity bills and poorer power quality if the renewable energy sources are limited, while the availability of more renewable energy sources will compensate for the negative effects of using renewable energy sources. [ABSTRACT FROM AUTHOR]