Energy efficient hourly scheduling of multichiller systems using imperialistic competitive algorithm Abstract   The hourahead optimization of the multichiller systems is necessary in order to minimize their power consumption and save energy. In this paper, an imperialistic competitive algorithm based optimal chiller loading problem is solved to find the partial load ratio, cooling flux, and the electricity requirement of the chillers and minimize the energy consumption of the whole system. The proposed approach simulates the sociopolitical competition using the initial population composed of the colonies and imperialists. The empires with their relative colonies and imperialists compete with each other to collapse the weakest empire and dominate the most powerful one achieving the minimum power consumption. The cooling capacity of the chillers and balance constraint are satisfied in hourly economic dispatch process. The optimization problem is tested on three standard systems. The imperialistic competitive algorithm based optimal chiller loading method finds better operating points for chillers than those obtained by recently published strategies.

RealTime Multiobjective Microgrid Power Management Using Distributed Optimization in an AgentBased Bargaining Framework In this paper, we propose a multiobjective power management procedure for microgrids (MGs). Through this procedure the power management problem is modeled as a bargaining game among different agents with different sets of objective functions. Nash bargaining solution (NBS) is employed to find the solution of the bargaining game. NBS lies on the Paretofront of the power management problem. Moreover, it introduces a unique and fair balance among the objective functions of different agents and removes the need to track the whole Paretofront in realtime. Distributed gradient algorithm is applied to find the NBS through a modular distributed decision framework without using a central control unit. In this way, the problem of data privacy of different parties within the MG is addressed. The proposed methodology has been tested through simulations on islanded and gridconnected MGs under different pricing scenarios (fixed versus timeofuse pricing).