利用插电式电动汽车在非住宅建筑中使用太阳能光伏系统进行调峰和填谷

K. N. Genikomsakis, Benjamin Bocquier, Sergio Lopez, C. Ioakimidis
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引用次数: 13

摘要

鉴于商业电力客户的能源成本通常取决于计费期内的实际消耗和峰值电力需求,本文研究了在大型非住宅建筑中利用插电式电动汽车(pev)和太阳能光伏(PV)系统进行调峰和填谷的概念。具体来说,它描述了一种混合方法,将用于太阳辐照度预测的人工神经网络(ANN)与MATLAB/Simulink模型相结合,以模拟太阳能光伏系统的功率输出,以及开发一个数学模型来控制电动汽车的充放电过程。通过对某高校建筑能耗的仿真,以及某高校停车场的停车占用实验数据,验证了该方法的适用性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilizing plug-in electric vehicles for peak shaving and valley filling in non-residential buildings with solar photovoltaic systems
This paper examines the concept of utilizing plug-in electric vehicles (PEVs) and solar photovoltaic (PV) systems in large non-residential buildings for peak shaving and valley filling the power consumption profile, given that the energy cost of commercial electricity customers typically depends on both actual consumption and peak power demand within the billing period. Specifically, it describes a hybrid approach that combines an artificial neural network (ANN) for solar irradiance forecasting with a MATLAB/Simulink model to simulate the power output of solar PV systems, as well as the development of a mathematical model to control the charging/discharging process of the PEVs. The results obtained from simulating the case of the power consumption of a university building, along with experimental parking occupancy data from a university parking lot, demonstrate the applicability and effectiveness of the proposed approach.
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