Optimal energy scheduling of a standalone rural microgrid for reliable power generation using renewable energy resources

ABSTRACT

Rural villages can be electrified using renewable power sources for the area to grow effectively. Microgrids powered by renewable energy is more environmentally friendly and practical choices for electrifying rural areas. This study attempts to ascertain the technological and financial viability of an autonomous hybrid energy source for a remote Indian area in order to provide a reliable power supply. The region’s load requirements can be met with the help of a solar energy system, biogas, wind energy, diesel generators, and batteries. Differential evaluation (DE) is used to optimize the proposed microgrid for grid-independent operation. The system’s ultimate objective is to reduce energy costs and recommend workable component configurations. Particle swarm optimization (PSO) and the genetic algorithm (GA) are used to compare the DE findings. The finding suggested the optimal energy cost of 0.22 $/kWh, a net current cost of $5,18,656, and a capital cost of $8,50,774. DE’s total net present cost is 4.3% less than PSO and 5.2% less than GA. However, it has been determined that the recommended approach is more practical and affordable for electrifying rural areas.

KEYWORDS:

• Microgrid
• optimal planning
• renewable energy
• optimization
• sizing
• rural electrification
• sensitivity

Nomenclature

GOA	=	Grasshopper optimization algorithm
PSO	=	Particle swarm optimization
GA	=	Genetic algorithm
GWO	=	Grey wolf optimization
HHO	=	Harris hawk optimization
HOMER	=	Hybrid optimization of multiple energy systems
$P{V}_{power}$	=	PV output power(kW)
$P_{rated}$	=	PV-rated power(kW)
MPSO	=	Multi-objective particle swarm optimization
$f_{pv}$	=	PV derating factor
$	=	US Doller
$I_T$	=	Solar radiation incident on PV array
$D{G}_c$	=	Diesel generator cost ($)
$F_c$	=	Fuel cost($/l)
$C_c$	=	Capital cost ($)
NOCT	=	Nominal operating cell temperature (℃)
$V_{mp}$	=	Optimum operating voltage(V)
$V_{sc}$	=	Open circuit voltage(V)
${\alpha }_p$	=	Temperature coefficient
$I_{st}$	=	Solar radiations (kW/m2)
$T_{cel}$	=	Cell temperature (℃)
$T_s$	=	Cell temperature
${ }_{\eta PV}$	=	Efficiency of PV (%)
$V_{bg}$	=	Calorific value of biogas
${ }_{bg}$	=	Biogas generator efficiency (%)
$N_{WT}$	=	number of wind turbine
U_HC	=	Unburned hydrocarbon
${\rho }_a$	=	Density (Kg/m3)
$A_{WT}$	=	Total swept area(m2)
$V\left(t\right)$	=	Velocity at time t(m/s)
$P{V}_c$	=	Photovoltaic panel cost ($)
$BA{T}_c$	=	Battery cost ($)
$D{R}_c$	=	Discount rate (%)
LPSP	=	Loss of power system probability
$I_{mp}$	=	Optimum operating current(A)
$I_{sc}$	=	Short circuit current(A)

Acknowledgment

For their assistance in conducting this research, the UGC (MANF) and Aligarh Muslim University, Aligarh, are gratefully acknowledged by the authors.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The current study makes no use of any scientific datasets. Information, facts, and figures are correctly mentioned in the present work and added to the references.