Water Cycle Algorithm (WCA): A New Technique to Harvest Maximum Power from PV

Renewable energy or alternative energy is extracted through renewable resources. These are considered as an alternative from conventional fossil fuel-based sources because conventional energy sources are depleting rapidly and raised concerns over increasing environmental impacts. Among many renewable sources, solar energy has a substantial part to meet the increased energy demand with reduced environmental effects. Solar irradiance and temperature are key factors upon which photovoltaic (PV) power generation depends but its optimum operating point gets affected by variation in the above-mentioned environmental factors. Finding the optimum operating point is a challenge due to the nonlinear solar behavior and varying nature of environmental conditions. To overcome these challenges, maximum power point (MPP) searching algorithms are exploited to get optimum power from the PV energy system. Maximum power point tracking (MPPT) behavior is different for various weather conditions, for instance, partial shading (PS), and uniform irradiance (UI) conditions. Numerous MPPT methods came to be used to find the optimum power. This work deals with the development of a novel technique for MPP finding of a PV system on the basis of the Water Cycle Algorithm (WCA) under PS conditions. It turns out to be good in terms of exploration and exploitation. Thus, it has the capability to avoid getting stuck in local minima (LM) and to find the global maxima (GM). The performance of the WCA technique is examined on four different types of P-V patterns for UI, PS and fast changing environmental conditions through MATLAB simulation and experimental setup. The findings of WCA are compared with the previous well-known soft computing methods such as PSO, ACS, DFO, and conventional method P&O to evaluate performance. The outcomes reveal that the WCA algorithm overtakes P&O from the perspective of robustness, accuracy, efficiency, and stability, as well as PSO in respect of converging speed and efficiency.