Inter-hours rolling scheduling of behind-the-meter storage operating systems using electricity price forecasting based on deep convolutional neural network-Reference-Cited by-同舟云学术

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Inter-hours rolling scheduling of behind-the-meter storage operating systems using electricity price forecasting based on deep convolutional neural network

Published:2021-02 Issue: Volume:125 Page:106499
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Deng Zhuofu,Liu Chenxu,Zhu Zhiliang

Funder

State Grid Corporation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference42 articles.

1. Analysis and experimental implementation of grid frequency regulation using behind-the-meter batteries compensating for fast load demand variations;Kim;IEEE Trans Power Syst,2016

2. Electricity price prediction based on hybrid model of adam optimized lstm neural network and wavelet transform;Chang;Energy,2019

3. Promoting behind-the-meter battery storage: Options for more effective government support and regulation;Tidemann;Int J Technol Intell Plan,2018

4. Wu D, Kintner-Meyer M, Yang T, Balducci P. Economic analysis and optimal sizing for behind-the-meter battery storage. In: 2016 IEEE Power and Energy Society General Meeting (PESGM), IEEE; 2016. p. 1–5.

5. Day-ahead electricity price forecasting and scheduling of energy storage in lmp market;Alam;IEEE Access,2019

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