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Optimal probabilistic operation management of smart parking lot and renewable sources in microgrid to reduce cost and improve system reliability considering demand response program

机译:微电网中智能停车场和可再生源的最佳概率运行管理,以降低考虑需求响应计划的成本和提高系统可靠性

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摘要

In this article, a new probabilistic operation management model for a microgrid (MG) with renewable sources such as solar and wind and also smart parking lots (PLs) is proposed. The model is based on demand response programing (DRP) with considering renewable sources and PLs uncertainties. An innovative scenario-based weighted objective function is proposed for the MG energy management system. The objective function is a combination of MG operation cost and the energy not supplied (ENS) fines for each scenario. Scenarios are weighted according to the probability of their occurrence in the objective function, so that more probable scenarios have a greater impact on the final cost. The generic Monte Carlo simulation (MCS) is used for generating the scenarios. For the proposed energy management model, the reliability index called loss of power supply probability (LPSP) is considered as a constraint. Also, the modified version of lightning search algorithm (LSA) is used due to higher accuracy. The proposed method is tested on the IEEE 33-bus test system. The simulation results indicated the good performance of the proposed method.
机译:在本文中,提出了一种具有可再生资源的微电网(MG)的新概率操作管理模型,例如太阳能和风以及智能停车场(PLS)。该模型基于需求响应课程(DRP),考虑可再生来源和PLS不确定性。为MG能量管理系统提出了一种创新的基于方案的加权目标函数。目标函数是MG运营成本的组合,以及每个场景的未提供(ENS)罚款的能量。情景根据其在目标函数中发生的概率而加权,因此更可能的情景对最终成本产生了更大的影响。通用蒙特卡罗模拟(MCS)用于生成方案。对于所提出的能量管理模型,称为电源概率(LPSP)的可靠性指数被认为是一个约束。此外,由于更高的精度,使用了闪电搜索算法(LSA)的修改版本。该方法在IEEE 33总线测试系统上进行了测试。仿真结果表明了该方法的良好性能。

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