PSO based Power Management in PV based Microgrids

Abstract

 Microgrids and distributed generation (DG) are currently receiving significant attention in 
research due to the potential advantages offered by renewable energy sources. A microgrid typically 
consists of renewable microsources located in close proximity to the load center. For effective 
operation, a microgrid requires a Voltage-Frequency control and Power management plan to regulate 
the actual and reactive power of each Distributed Generation (DG) source. This study examines the 
impact of incorporating renewable energy into the distribution system on load- sharing. This paper 
presents a Genetic Algorithm-based Maximum Power Point Tracking (MPPT) technique for a 
standalone photovoltaic (PV) array connected to a Battery Energy Storage System (BESS). Solar 
irradiance and temperature have an impact on the generation of photovoltaic (PV) energy, specifically 
in relation to maximum power point tracking (MPPT). As a result of technological advancements, 
the output of photovoltaic (PV) systems varies, and the presence of nonlinear demand exacerbates 
the situation. The PSO-based Maximum Power Point Tracking (MPPT) algorithm is effective for 
achieving local optimization in photovoltaic (PV) power generation. DC/DC converters and boost 
converters were utilized to attain the desired rated voltage. A PI controller regulates the DC-link 
voltage to stay close to its reference value, irrespective of external factors.