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Incorporating User Utility in a Smart Microgrid with Distributed Generation and Elastic Demand

机译:在智能微电网中纳入用户实用程序,具有分布式发电和弹性需求

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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)将在创建低碳未来的途径方面发挥重要作用。 MicroGrids是智能电网(SG)框架内的DSM的理想测试床,允许增加分布式发电(DG)的集成,这里集中在分布式可再生能源(RESS)上。现有工作采用保守估计来模拟ress的随机性质,导致模拟结果中的不准确性。用户特定参与DSM程序的大不确定性存在。本文开发了灵活的能量负载功能,有效地将不同的用户的行为模式纳入DSM框架。通过使用预期的成本函数来准确地将预测的风速放电到电力输出,通过使用预期的成本函数来减少将小型风发电连接到智能微电网中的不确定性。通过使用伪随机数发生器,在每个时隙内的许多子视野中的实际风速在众多子视野上变化。有效管理可再生生成的随机性,产生稳健的模拟。研究了模型敏感性,并提出了图形结果。

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