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Incorporating user utility in a smart microgrid with distributed generation and elastic demand

机译:将用户实用程序整合到具有分布式发电和弹性需求的智能微电网中

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Demand Side Management (DSM) will play a large role in creating a pathway to a low carbon future. Microgrids are an ideal test bed for DSM within the Smart Grid (SG) framework, allowing for increased integration of distributed generation (DG), here focused on distributed Renewable Energy Sources (RESs). Existing work uses conservative estimates to model the stochastic nature of RESs, resulting in inaccuracies in simulation results. Large uncertainty in user specific participation in DSM programs exists. This paper develops a flexible energy load function, effectively incorporating different user's behaviour patterns into the DSM framework. Uncertainty in connecting small-scale wind generation into the smart microgrid is reduced by using an expected cost function to accurately map predicted wind speed to power output. Actual wind speed is varied across numerous sub-horizons within each time slot by using a pseudo-random number generator. The stochastic nature of renewable generation is effectively managed, producing a robust simulation. Model sensitivities are investigated and graphical results presented.
机译:需求方管理(DSM)将在创建通往低碳未来的途径中扮演重要角色。微电网是DSM在智能电网(SG)框架内的理想测试平台,可以增强分布式发电(DG)的集成,这里的分布式发电主要集中于分布式可再生能源(RESs)。现有工作使用保守估计来建模RES的随机性质,从而导致模拟结果不准确。用户特定参与DSM计划存在很大的不确定性。本文开发了一种灵活的能量负载功能,可以将不同用户的行为模式有效地整合到DSM框架中。通过使用预期成本函数将预测的风速准确映射到功率输出,可以减少将小型风力发电连接到智能微电网的不确定性。通过使用伪随机数生成器,实际风速在每个时隙中的多个子视点范围内都会变化。可再生能源的随机性得到有效管理,从而产生了可靠的仿真结果。模型敏感性进行了调查,并提出了图形结果。

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