A Multi-Objective Optimization Approach towards a Proposed Smart Apartment with Demand-Response in Japan

被引:19
作者
Susowake, Yuta [1 ]
Masrur, Hasan [1 ]
Yabiku, Tetsuya [1 ]
Senjyu, Tomonobu [1 ]
Motin Howlader, Abdul [2 ]
Abdel-Akher, Mamdouh [3 ,4 ]
Hemeida, Ashraf M. [5 ]
机构
[1] Univ Ryukyus, Fac Engn, Nakagami, Okianwa 9030213, Japan
[2] Univ Hawaii, Dept Elect Engn, 1680 East West Rd, Honolulu, HI 96822 USA
[3] Aswan Univ, Fac Engn, Dept Elect Engn, Aswan 81542, Egypt
[4] Qassim Univ, Unaizah Coll Engn, Dept Elect Engn, Unaizah 56453, Saudi Arabia
[5] Aswan Univ, Fac Energy Engn, Dept Elect Engn, Aswan 51528, Egypt
关键词
smart apartment; photovoltaic; multi-objective optimization; demand-response; real-time pricing; NSGA-II; SYSTEM; STORAGE; DESIGN;
D O I
10.3390/en13010127
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
In Japan, residents of apartments are generally contracted to receive low voltage electricity from electric utilities. In recent years, there has been an increasing number of high voltage batch power receiving contracts for condominiums. In this research, a high voltage batch receiving contractor introduces a demand-response in a low voltage power receiving contract, which maximizes the profit of a high voltage batch receiving contractor and minimizes the electricity charge of residents by utilizing battery storage, electric vehicles (EV), and heat pumps. A multi-objective optimization algorithm calculates a Pareto solution for the relationship between two objective trade-offs in the MATLAB (R) environment.
引用
收藏
页数:14
相关论文
共 22 条
[1]  
Deb K., 2001, Multi-objective optimization using evolutionary algorithms, P239
[2]   Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR [J].
Erdinc, Ozan ;
Paterakis, Nikolaos G. ;
Mendes, Tiago D. P. ;
Bakirtzis, Anastasios G. ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (03) :1281-1291
[3]   Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households [J].
Erdinc, Ozan .
APPLIED ENERGY, 2014, 126 :142-150
[4]   Optimized energy consumption model for smart home using improved differential evolution algorithm [J].
Essiet, Ima O. ;
Sun, Yanxia ;
Wang, Zenghui .
ENERGY, 2019, 172 :354-365
[5]   Model Predictive Control Home Energy Management and Optimization Strategy with Demand Response [J].
Godina, Radu ;
Rodrigues, Eduardo M. G. ;
Pouresmaeil, Edris ;
Matias, Joao C. O. ;
Catalao, Joao P. S. .
APPLIED SCIENCES-BASEL, 2018, 8 (03)
[6]   Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming [J].
Kamjoo, Azadeh ;
Maheri, Alireza ;
Dizqah, Arash M. ;
Putrus, Ghanim A. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 74 :187-194
[7]   Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies [J].
Liu, Chunhua ;
Chau, K. T. ;
Wu, Diyun ;
Gao, Shuang .
PROCEEDINGS OF THE IEEE, 2013, 101 (11) :2409-2427
[8]   Price-Controlled Energy Management of Smart Homes for Maximizing Profit of a GENCO [J].
Rahmani-Andebili, Mehdi ;
Shen, Haiying .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2019, 49 (04) :697-709
[9]   Multi-Objective Optimization and Design of Photovoltaic-Wind Hybrid System for Community Smart DC Microgrid [J].
Shadmand, Mohammad B. ;
Balog, Robert S. .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (05) :2635-2643
[10]   A Stochastic Home Energy Management System Considering Satisfaction Cost and Response Fatigue [J].
Shafie-Khah, Miadreza ;
Siano, Pierluigi .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (02) :629-638