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Day-ahead scheduling problem of smart micro-grid with high penetration of wind energy and demand side management strategies

机译:智能微电网的智能微电网的一天调度问题,风能和需求副管理策略

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摘要

In this paper, the day-ahead scheduling problem of a smart microgrid (SMG) is modeled as a multi-objective function consisting of: i) minimizing the operation cost and the emission pollution in generation side ii) minimizing the load curtailment cost with the strategic conversion of curtailable loads (CLs) and iii) coordinating of shiftable loads (SLs) and the output power of wind turbines (WTs). The second and the third objectives present a new approach of Demand Side Management (DSM) strategies to improve the customer's satisfaction (CS) and the WT penetration (WTP) using stimulation of customers to use their loads regarding the demand profile of the system. Also, the output power of WTs is considered as the stochastic model, and the participation of the SLs based on the availability of WTs output power are scheduled. To confirm the proposed approach, all objective functions are optimized by the epsilon-constraint approach in the GAMS optimization software and the best solution of the non-dominated Pareto solutions is selected using the decision-making method. To investigate the effectiveness of the proposed model, it is applied on a 24-node microgrid through four case studies.
机译:在本文中,智能微电网(SMG)的一天前方调度问题被建模为包括:i)最小化Maile侧II的操作成本和发射污染,最小化负载缩减成本可缩税负载(CLS)和III)的战略转换,可转载负载(SLS)和风力涡轮机(WTS)的输出功率。第二个和第三个目标呈现了一种新的需求侧管理方法(DSM)策略,以改善客户的满意度(CS)和WT渗透(WTP)使用刺激客户来利用其对系统的需求配置文件的负载。而且,WTS的输出功率被认为是随机模型,并根据WTS输出功率的可用性进行SLS的参与。为了确认所提出的方法,所有客观函数都是通过GAMS优化软件中的ePSILON - 约束方法进行优化,并使用决策方法选择非主导的帕累托解决方案的最佳解决方案。为了研究所提出的模型的有效性,它通过四个案例研究应用于24节点微电网。

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