Abstract:
The microgrid is a new genre of integrating the distributed energy resources
(DER) within the grid. However, literature studies with the consideration of
RERs uncertainty and DRPs of grid-connected EVs integrated residential PVWT-FC-DE based community rural microgrid (MG) by employing single
objective problem using ABC/PSO algorithms is missing. This work modeled
a household energy management comprising of microgrid (MG) system and
DRPs. Residential loads with price-based tariffs are introduced for reduction
in peak load demands and energy costs. For modeling uncertainties in RERs,
their stochastic nature is modeled with probabilistic method. In this paper, a
joint optimization approach is proposed for the optimal planning and operation
of grid-connected residential rural MG integrated to renewable energy and
electric vehicles (EVs) in view of DRPs. The investigation focuses on energy
saving of residential homes under different DRPs and RERs integration. The
EVs are integrated to MG by including photovoltaic (PV), wind turbines (WT),
fuel cell (FC) and diesel engine (DE). A multi objective optimization problem
has been formulated to minimize the Operating Cost, Pollutant Treatment Cost
and Carbon Emissions Cost defined as C1, C2, and C3 respectively. The load
demand has been rescheduled in view of three DRPs i.e., critical peak pricing
(CPP), real time electricity pricing (RTEP), time of use (TOU). Further, the
EV load has also been analyzed in the form of autonomous and coordinated
charging strategies. The proposed multi objective problem is transformed into
a single objective problem using artificial bee colony (ABC) algorithm and the
results are compared with particle swarm optimization (PSO) algorithm. The
simulation analysis was accomplished employing ABC and PSO in MATLAB.
The mathematical model of MG was implemented, and the effects of DRPs
based MG were investigated under different number of EVs and load data inviii
terms of reducing different costs. To analyze the impact of DRPs, the
residential rural MG is implemented for 50 homes with a peak load of 5 kW
each and EV load with 80 EVs and 700 EVs respectively. The simulation
results with the total 32 test cases are formulated, while analyzing the tradeoff
between ABC and PSO algorithms. The simulation analysis shows that
multiple DRPs, EVs, and RERs offered substantial trade-off.
