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Study of the Effect of Time-Based Rate Demand Response Programs on Stochastic Day-Ahead Energy and Reserve Scheduling in Islanded Residential Microgrids

机译:基于时间的速率需求响应方案对随机日前能源和储备调度的时间为基于率需求响应方案的研究

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In recent deregulated power systems, demand response (DR) has become one of the most cost-effective and efficient solutions for smoothing the load profile when the system is under stress. By participating in DR programs, customers are able to change their energy consumption habits in response to energy price changes and get incentives in return. In this paper, we study the effect of various time-based rate (TBR) programs on the stochastic day-ahead energy and reserve scheduling in residential islanded microgrids (MGs). An effective approach is presented to schedule both energy and reserve in presence of renewable energy resources (RESs) and electric vehicles (EVs). An economic model of responsive load is also proposed on the basis of elasticity factor to model the behavior of customers participating in various DR programs. A two-stage stochastic programming model is developed accordingly to minimize the expected cost of MG under different TBR programs. To verify the effectiveness and applicability of the proposed approach, a number of simulations are performed under different scenarios using real data; and the impact of TBR-DR actions on energy and reserve scheduling are studied and compared subsequently.
机译:在最近的解调电力系统中,需求响应(DR)已成为最具成本效益和有效的解决方案之一,在系统处于应力时平滑负载曲线。通过参加DR计划,客户能够根据能源价格变动改变其能源消耗习惯,并以换取激励。在本文中,我们研究了各个基于时间的速率(TBR)计划对住宅岛屿微电网(MGS)的随机日期能源和储备调度的影响。提出了一种有效的方法,以在可再生能源(RESS)和电动车(EVS)存在下提高能量和储备。在弹性因素的基础上还提出了一种响应载荷的经济模型,以模拟参与各种DR程序的客户行为。相应地开发了两阶段随机编程模型,以最小化不同TBR程序下MG的预期成本。为了验证所提出的方法的有效性和适用性,使用真实数据的不同场景下进行许多模拟;研究了TBR-DR动作对能源和储备调度的影响,并随后进行比较。

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