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Energy mix optimization is considered an essential tool for assessing the efficacy of renewable energy system (RES). Countless approaches have been employed by grid planning engineers and scientists to optimally size grid-connected photovoltaic (PV) systems. Optimizing grid-connected PV systems is beneficial since it causes a reduction in the energy produced by the conventional power plants, and as a result, a reduction in the harmful emissions that are released as by-products. In this study, a large commercial load in the city of Makkah in Saudi Arabia is connected to an optimally designed grid-connected PV systems with the support of a battery storage system (BSS). First, using HOMER software, the system components are chosen by considering the electrical and economic variables. A comparative investigation is carried out for three configuration systems along with the detailed technical study for the proposed systems. Simulation results recommend utilizing a battery system and RES with a minimum cost of energy (COE) of $0.11. Using both HOMER and MATLAB, the PV, converter, and battery system optimal size are estimated by considering the net present cost (NPC), COE, excess electricity and energy savings, emissions, and renewable penetration ratio to find the most economical and environmental-friendly combination. The results show that 1.60 MW is the optimal capacity of each PV, converter, and battery BSS elements to achieve the minimum targeted emission and COE, which resulted in a reduction in the overall NPC of the scheme. When the optimal design is configurated, it is found that the unmet load is zero. [ABSTRACT FROM AUTHOR]

This paper discusses maximum power point tracking (MPPT) methods of PV system for normal and partial shading conditions (PSC). The selected MPPT methods were classified as artificial intelligent, hybrid, and other MPPT methods. The comparison of researches on MPPT methods under normal condition and PSC reveals that researchers have concentrated more on shading conditions since the last few years mainly due to the need of power output and efficiency improvements. It is believed that the information contained in this piece of work will be of great use for the researchers in the field under consideration. [ABSTRACT FROM AUTHOR]

Certain environmental conditions such as accumulation of dust and change in weather conditions affect the amount of solar radiation received by photovoltaic (PV) panel surfaces and thus have a significant effect on panel efficiency. This study conducted an experimental investigation in Surabaya, Indonesia, on the effect of these factors on output PV power reduction from the surface of a PV module. The module was exposed to outside weather conditions and connected to a measurement system developed using a rule-based model to identify different environmental conditions. The rule-based model, a clear sky solar irradiance model that included solar position, and a PV temperature model were then used to estimate the PV output power, and tests were also conducted using an ARM Cortex-M4 microcontroller STM32F407 as a standalone digital controller equipped with voltage, current, temperature, and humidity sensors to measure real time PV output power. In this system, humidity was monitored to identify dusty, cloudy, and rainy conditions. Validated test results demonstrate that the prediction error of PV power output based on the model is 3.6% compared to field measurements under clean surface conditions. The effects of dust accumulation and weather conditions on PV panel power output were then analyzed after one to four weeks of exposure. Results revealed that two weeks of dust accumulation caused a PV power output reduction of 10.8% in an average relative humidity of 52.24%. Results of the experiment under rainy conditions revealed a decrease in PV output power of more than 40% in average relative humidity of 76.32%, and a decrease in output power during cloudy conditions of more than 45% in an average relative humidity of 60.45% was observed. This study reveals that local environmental conditions, i.e., dust, rain, and partial cloud, significantly reduce PV power output. [ABSTRACT FROM AUTHOR]

The tilt angle of photovoltaic (PV) panels is a major factor affecting the amount of solar radiation falling on the panel surface. The optimum tilt angle depends on the position of the sun, latitude and local geographical characteristics. This paper investigates PV panel optimum tilt angles for various cities in the Kingdom of Saudi Arabia. For simulation purposes, horizontal solar radiation data for the study cities was obtained from NASA. MATLAB software was used to optimize tilt angle by maximizing solar radiation. Experiments were conducted to validate the theoretical requirement for negative tilt angles during summer. Results demonstrate that adjusting tilt angles six times per year harvests 99.5% of the solar radiation that could be attained with daily PV panel adjustment. [ABSTRACT FROM AUTHOR]

This work proposes a modified differential evolution (MDE) based maximum power point tracker (MPPT) for photovoltaic (PV) system under partial shading condition. The proposed MDE does not involve any random numbers; hence, consistency of MPP tracking always prevails. Besides, it only contains one tuning parameter, i.e., mutation factor, which significantly simplifies the implementation strategy and therefore a low-cost micro-controller can be used for its realization. Despite the simpler MPPT structure, for each tested shaded curve, MDE always converges toward the global MPP within 12 perturbations. Performance wise, it outperforms another evolutionary algorithm, namely particle swarm optimization (PSO), which frequently traps at local MPP in shading conditions. The proposed MDE also works accurately for the measured data profile of a tropical country during 9.00 am to 5.00 pm, where it attains 99.5% average tracking efficiency. [ABSTRACT FROM AUTHOR]

Resource optimization is a major factor in the assessment of the effectiveness of renewable energy systems. Various methods have been utilized by different researchers in planning and sizing the grid-connected PV systems. This paper analyzes the optimal photovoltaic (PV) array and inverter sizes for a grid-connected PV system. Unmet load, excess electricity, fraction of renewable electricity, net present cost (NPC) and carbon dioxide (CO 2 ) emissions percentage are considered in order to obtain optimal sizing of the grid-connected PV system. An optimum result, with unmet load and excess electricity of 0%, for serving electricity in Makkah, Saudi Arabia is achieved with the PV inverter size ratio of R = 1 with minimized CO 2 emissions. However, inverter size can be downsized to 68% of the PV nominal power to reduce the inverter cost, and hence decrease the total NPC of the system. [ABSTRACT FROM AUTHOR]