KU-MG1: A Dataset for Hybrid Photovoltaic-Natural Gas Generator Microgrid Model of a Residential Area. (For Nirala residential area, Khulna, Bangladesh)

Published: 28-07-2020| Version 1 | DOI: 10.17632/4tmsmp98tr.1
Contributors:
Abdullah-Al Nahid,
md. sajid jaman,
Md. Arif-Ar- Rafi,
Md Nazmul Hasan,
M A Parvez Mahmud

Description

A renewable energy resource-based sustainable microgrid model for a residential area is designed by HOMER PRO microgrid software. A small-sized residential area of 20 buildings of about 60 families with 219 MWh and an electric vehicle charging station of daily 10 batteries with 18.3MWh annual energy consumption considered for Nirala residential area, Khulna (22°48.0'N, 89°33.4'E) is selected as our case study. Solar panels, natural gas generator, inverter and Li-ion batteries are required for our proposed model. The HOMER PRO microgrid software is used to optimize our designed microgrid model. Data were collected from HOMER PRO for the year 2007. We have compared our daily load demand 650KW with the results varying the load by 10%, 5%, 2.5% more and less to find out the best case according to our demand. We have a total of 7 different datasets for different load conditions where each dataset contains a total of 8760 sets of data having 6 different parameters for each set. Data file contents: Data 1:: original_load.csv: This file contains data for 650KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Data arrangement is given below: Column 1: Date and time of data recording in the format of MM-DD- YYYY [hh]:[mm]. Time is in 24-hour format. Column 2: Solar power output in KW unit. Column 3: Generator power output in KW unit. Column 4: Total Electrical load served in KW unit. Column 5: Excess electrical production in KW unit. Column 6: Li-ion battery energy content in KWh unit. Column 7: Li-ion battery state of charge in % unit. Data 2:: 2.5%_more_load.csv: This file contains data for 677KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset. Data 3:: 2.5%_less_load.csv: This file contains data for 622KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset. Data 4:: 5%_more_load.csv: This file contains data for 705KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset. Data 5:: 5%_less_load.csv: This file contains data for 595KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset. Data 6:: 10%_more_load.csv: This file contains data for the 760KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset. Data 7:: 10%_less_load.csv: This file contains data for 540KW load demand. The dataset contains a total of 8760 sets of data having 6 different parameters for each set. Column information is the same for every dataset.

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