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 ε-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.

本文将智能微电网（SMG）的日前调度问题建模为一个多目标函数，包括：i）最小化运营成本和发电侧的排放污染； ii）最小化负荷削减成本，同时实现可削减负荷（CLs）的战略转换，以及iii）协调可转移负荷（SLs）和风力涡轮机（WTs）的输出功率。第二个目标和第三个目标提出了一种需求方管理（DSM）策略的新方法，以利用客户的刺激来使用他们的有关系统需求概况的负载，从而提高客户满意度（CS）和WT渗透率（WTP）。另外，WT的输出功率被认为是随机模型，并且基于WT的输出功率的可用性来调度SL的参与。为了确认提出的方法，在GAMS优化软件中通过ε约束方法对所有目标函数进行了优化，并使用决策方法选择了非支配Pareto解的最佳解。为了研究提出的模型的有效性，通过四个案例研究将其应用于24节点微电网。