Dynamic Residential Energy Management for Real-Time Pricing

被引：7

作者：

Yao, Leehter ^{[1
]}

Hashim, Fazida Hanim ^{[2
]}

Lai, Chien-Chi ^{[1
]}

机构：

[1] Natl Taipei Univ Technol, Dept Elect Engn, Taipei 10608, Taiwan

[2] Natl Univ Malaysia, Fac Engn & Built Environm, Bangi 43600, Selangor, Malaysia

来源：

ENERGIES | 2020年 / 13卷 / 10期

关键词：

fuzzy controller; home energy management system; genetic algorithm; photovoltaic panel; real-time price; ADAPTIVE FUZZY CONTROLLER; RENEWABLE ENERGY; SYSTEM; OPTIMIZATION; DESIGN; LOAD; STORAGE;

D O I：

10.3390/en13102562

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

A home energy management system (HEMS) was designed in this paper for a smart home that uses integrated energy resources such as power from the grid, solar power generated from photovoltaic (PV) panels, and power from an energy storage system (ESS). A fuzzy controller is proposed for the HEMS to optimally manage the integrated power of the smart home. The fuzzy controller is designed to control the power rectifier for regulating the AC power in response to the variations in the residential electric load, solar power from PV panels, power of the ESS, and the real-time electricity prices. A self-learning scheme is designed for the proposed fuzzy controller to adapt with short-term and seasonal climatic changes and residential load variations. A parsimonious parameterization scheme for both the antecedent and consequent parts of the fuzzy rule base is utilized so that the self-learning scheme of the fuzzy controller is computationally efficient.

引用

页数：15

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