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Appl. Sci. 2015, 5(3), 516-531;

Hybrid Energy Scheduling in a Renewable Micro Grid

1,* , 1,†
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
School of Economics and Management, North China Electric Power University, Beijing 102206, China
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Minho Shin
Received: 14 July 2015 / Revised: 25 August 2015 / Accepted: 28 August 2015 / Published: 8 September 2015
(This article belongs to the Special Issue Smart Grid: Convergence and Interoperability)
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In this paper, we address the energy scheduling issue in a hybrid energy micro grid, which consists of photovoltaic (PV), wind power, combined heat and power (CHP), energy storage and electric vehicles (EVs). The optimal scheduling model of these power sources is presented with consideration of the demand response. The objective function is minimum total operation costs, including gas cost, electric power purchase from the main grid and storage and EV charging-discharging costs. In the process of optimization, multi-team particle swarm optimization (MTPSO) is proposed, which uses units, groups and swarm information to update the velocity (position) with faster and more stable convergence. With simulation analysis, it is found that the proposed model is effective, and the presented MTPSO has a better global search ability than PSO. View Full-Text
Keywords: micro grid; scheduling; hybrid energy micro grid; scheduling; hybrid energy

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Liu, Z.; Chen, C.; Yuan, J. Hybrid Energy Scheduling in a Renewable Micro Grid. Appl. Sci. 2015, 5, 516-531.

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