<![CDATA[The availability of fossil energy sources decreases as consumers' demand for electrical energy increases rapidly. Currently, the utilization of renewable energy sources is crucial. PV is a renewable energy source that converts photon energy into DC current. Maximum power point tracker (MPPT) control technology for photovoltaics has advanced significantly. PV is unique in that its P-V characteristic curve is non-linear. Conditions of partial shading can cause the P-V curve to have multiple peaks. This research will design MPPT PV using the Particle Swarm Optimization (PSO) algorithm in partially shaded conditions with an Arduino Uno and boost converter. Conventional algorithms, incremental conductance (IC), and Perturb and Observe (P&O) are implemented as a comparison. The purpose of implementing the PSO algorithm is to find the global peak of power to minimize power losses of PV. It leads to optimal power in case of partial shading conditions. Two PV modules are arranged in series for MPPT in a partially shaded environment. The examination was conducted in a darkened room with spotlights. The mean absolute percentage error of the current sensor, INA219, and the voltage sensor, voltage divider, was less than 1% during testing. The MPPT PV system test results indicate that the PSO algorithm can extract approximately 1.64 Watts of average power. In contrast, the IC and P&O algorithms can extract about 1.25 Watts and 1.41 Watts, respectively. When no algorithm exists in the control system, the extracted power is approximately 1.13 watts. Thus, the PSO algorithm tracks global or optimal power under partial shading conditions.]]>
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