Abstract:
The research aims at defining and analyzing an energy solution that incorporates
renewable energy, thereby giving rise to improving energy security and providing grid
stability for the grid networks located in urban residential areas. The urbanization growth
in Botswana coincides with the increase in electricity consumption. The electricity load
demand in the country outlasts the local supply and thereby the need for importing
electricity from the Southern Africa Power Pool (SAPP). To address grid stability and
reliable power supply issues, the research aims to design a microgrid system for an urban
settlement by matching the electric load demand with solar photovoltaic (PV) generation
in a residential district. The initial stages of the research include measuring electrical loads
in a single household for a certain period. The energy data collected from residential
homes were subjected to a smart metering examination. The analysis revealed high
variability in the daily energy usage of the household. The dataset was tabulated through
the two seasons experienced in Botswana, summer, and winter. Following a study using
clustering techniques, three clusters with outliers’ data identified the optimum monthly
energy use with the lowest Mean Squared Error (MSE) after ten iterations. The peak
hourly profiles from the metered residential household were used to represent a
cumulative 250-kW planned power solar PV microgrid system. The design and simulation
were conducted on the simulation environment MATLAB/Simulink with real-time daily
irradiation and temperature profiles from the metered household location.
Proportional Integral Derivative (PID) controllers could achieve a desired DC microgrid
voltage throughout the day. The boost converter through a signal from the Maximal Power
Point Tracking (MPPT) could achieve the maximum voltage of the solar PV module. For
energy management optimization, Fuzzy Logic Control (FLC) was incorporated for the
grid-connected microgrid with battery support. The FLC simulation analysis
demonstrated that the battery offered energy stability inside the microgrid system during
the shift from island mode to a grid-connected mode of operation. The economic study
was conducted in HOMERPro, and it revealed the levelized cost of electricity at USD
10.90/ kWh. The nature of the solar PV microgrid design revealed the system's lifetime
cost savings worth USD 99,248.6. A microgrid system is a subpart of a smart grid; thus,
the proposed system aids in achieving the quick restoration of electricity when a power
outage occurs while also enhancing local energy resiliency.
Boitshoko, S (2024). Modeling,simulation and energy management of solar PV-based Microgrinds using real-time residential data. Afribary. Retrieved from https://afribary.com/works/modeling-simulation-and-energy-management-of-solar-pv-based-microgrinds-using-real-time-residential-data
Boitshoko, Seane "Modeling,simulation and energy management of solar PV-based Microgrinds using real-time residential data" Afribary. Afribary, 30 Mar. 2024, https://afribary.com/works/modeling-simulation-and-energy-management-of-solar-pv-based-microgrinds-using-real-time-residential-data. Accessed 05 Nov. 2024.
Boitshoko, Seane . "Modeling,simulation and energy management of solar PV-based Microgrinds using real-time residential data". Afribary, Afribary, 30 Mar. 2024. Web. 05 Nov. 2024. < https://afribary.com/works/modeling-simulation-and-energy-management-of-solar-pv-based-microgrinds-using-real-time-residential-data >.
Boitshoko, Seane . "Modeling,simulation and energy management of solar PV-based Microgrinds using real-time residential data" Afribary (2024). Accessed November 05, 2024. https://afribary.com/works/modeling-simulation-and-energy-management-of-solar-pv-based-microgrinds-using-real-time-residential-data