Next Article in Journal
Evaluating the Effect of Metal Bipolar Plate Coating on the Performance of Proton Exchange Membrane Fuel Cells
Next Article in Special Issue
Energy Storage Systems for Shipboard Microgrids—A Review
Previous Article in Journal
Co-Digestion of Napier Grass with Food Waste and Napier Silage with Food Waste for Methane Production
Previous Article in Special Issue
A Comparison of Non-Isolated High-Gain Three-Port Converters for Hybrid Energy Storage Systems
Open AccessArticle

Optimal Scheduling of Hybrid Energy Resources for a Smart Home

1
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea
2
Department of Electrical Engineering, Khwaja Fareed University of Engineering and Information Technology (KFUEIT), Rahim Yar Khan 64200, Pakistan
*
Author to whom correspondence should be addressed.
Energies 2018, 11(11), 3201; https://doi.org/10.3390/en11113201
Received: 29 September 2018 / Revised: 12 November 2018 / Accepted: 14 November 2018 / Published: 18 November 2018
(This article belongs to the Special Issue Analysis and Design of Hybrid Energy Storage Systems)
The present environmental and economic conditions call for the increased use of hybrid energy resources and, concurrently, recent developments in combined heat and power (CHP) systems enable their use at a domestic level. In this work, the optimal scheduling of electric and gas energy resources is achieved for a smart home (SH) which is equipped with a fuel cell-based micro-CHP system. The SH energy system has thermal and electrical loops that contain an auxiliary boiler, a battery energy storage system, and an electrical vehicle besides other typical loads. The optimal operational cost of the SH is achieved using the real coded genetic algorithm (RCGA) under various scenarios of utility tariff and availability of hybrid energy resources. The results compare different scenarios and point-out the conditions for economic operation of micro-CHP and hybrid energy systems for an SH. View Full-Text
Keywords: battery energy storage system (BESS); electric vehicle (EV); fuel cell (FC); micro combined heat and power (micro-CHP) system; real coded genetic algorithm (RCGA); smart home (SH) battery energy storage system (BESS); electric vehicle (EV); fuel cell (FC); micro combined heat and power (micro-CHP) system; real coded genetic algorithm (RCGA); smart home (SH)
Show Figures

Figure 1

MDPI and ACS Style

Rafique, M.K.; Haider, Z.M.; Mehmood, K.K.; Saeed Uz Zaman, M.; Irfan, M.; Khan, S.U.; Kim, C.-H. Optimal Scheduling of Hybrid Energy Resources for a Smart Home. Energies 2018, 11, 3201.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop