Forecasting and Scheduling of a Photovoltaic/Battery Energy Storage System for Load Demand

被引：0

作者：

Ozturk, Serkan ^{[1
]}

Cadirci, Isik ^{[1
]}

机构：

[1] Hacettepe Univ, Elekt & Elekt Muhendisligi Bolumu, Ankara, Turkey

来源：

2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU) | 2016年

关键词：

Photovoltaic Systems; Battery Storage Systems; Estimation of Energy Production; Smart Grids; Artificial Neural Networks; NEURAL-NETWORKS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Grid-connected photovoltaic systems are considered an attractive alternative source of energy production due to new developments in technology, increasing environmental pollution and excessive load density on transmission lines. Controlling the energy in a smart way, increasing the efficiency as well as revealing the concept of smart grid. Estimation of energy production, planning of household electrical appliances and applications to prevent overloading of transmission lines, plays an important role in the smart grid concept. Short-term load forecasting and management of the energy for large-scale systems such as national grids, provide great benefits. Implementation and estimation is more difficult for small-scale systems. In this paper, it is aimed to determine scheduling and energy estimation of a consumption center with photovoltaic-battery energy storage system.

引用

页码：2093 / 2096

页数：4

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