Publisher's Synopsis
Traditional energy resources are losing significance
due to global warming and the quick exhaustion of fossil fuels. Non- conventional
energy resources like solar, wind, biomass, etc, can be highly beneficial in the
upcoming days. Incorporating renewable energy sources (RES) with electric grids has
gained significant attention and poses several challenging issues among the research
community. The discontinuous and uncontrollable nature of solar energy surges the difficulty of
grid management and increases the difficulty in handling the production and utilization
of electrical energy. Accurate solar power prediction (SPP) models are necessary for optimal grid
stability management. The present model mostly concentrates on the solution and the predicting
parts that remain unaddressed. The Maximum Power Point Tracking (MPPT) lacks most of the
forecasting mechanism; hence it proves to be a generic model. The current MPPT models are
inefficient in tracking the maximum power point because of the sunshine variation. The
emergence of Artificial Intelligence (AI) technique and their adoption of
various techniques have designed more than one domain automatically.
The idea of Smart Grid (SG) combines consumer solutions quantity
of technologies and meets numerous regulatory drivers and policies. SG is the
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next generation power system which utilizes bi-directional flows of information and
electricity. The capacity of data amalgamation, reliable data communication, system monitoring,
secured data scrutiny, and supervisory and local controls of the SG could fulfil the
consumer-supplier demand needs like decline in the power utilization, cost of energy and enhance
the efficiency of
system. Figure 1.1 illustrates the concept of SGs.
