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Optimal Operation of Microgrid in the presence of Real-time Pricing Demand Response Program using Artificial Bee Colony Algorithm with a Modified Choice Function
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Shahram Kamali Nia *   |
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Abstract: (913 Views) |
| Abstract: Microgrid is one of the newest technologies in power systems. Microgrid can usually has a set of distributed energy resources that makes it able to operate separate from power grid. Optimal operation of microgrids means the optimal dispatch of power resources through day and night hours. This thesis proposed a new method for optimal operation of microgrid. In this method, real-time pricing demand response program is used shifting a part of load during different hours. Some distributed generation units such as wind, photovoltaic and diesel units are used for providing electrical load. Optimal operation of microgrid is modeled as an optimization problem in three cases: economic load dispatch, emission dispatch, and combined economic-emission dispatch. The objective function of problem for above cases is defined as minimizing cost of distributed generation, minimizing pollution emission and minimizing total costs including distributed generation and emission costs, respectively. For solve the optimization problem, a new method is used which named artificial bee colony algorithm with a modified choice function (MCF-ABC). This method is an improved version of original artificial bee colony (ABC) algorithm. Simulation is carried out for a sample microgrid in MATLAB environment. Simulation results show that demand response program not only decreases peak load and increases load factor, but also it can improve the microgrid operation through decreasing emission and costs. Results indicate that incorporating combined economic-emission dispatch model leads to better solutions for microgrid operation. Results also demonstrate that MCF-ABC method can improve microgrid function via reduction in costs and pollutions and then it has a better performance in the comparison of ABC method. |
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Full-Text [PDF 1131 kb]
(410 Downloads)
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Type of Study: Applicable |
Subject:
Special
Received: 2019/05/6 | Accepted: 2019/08/20 | Published: 2019/09/16
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