Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions - A Review

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system's overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015 - 2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions

Modeling of Chloride Binding Capacity in Cementitious Matrices Including Supplementary Cementitious Materials

The improvement in the chloride binding capacity of concrete has been shown to increase corrosion resistance. The addition of supplementary cementitious materials (SCMs) to Portland cement has been proven to increase the binding capacity, except for silica fume, whereas the impact of chemical additives is not extensively addressed in the literature. This work studies the influence of SCMs and chemical additives, i.e., calcium nitrite inhibitor (CNI), migrating corrosion inhibitor (MCI), and Caltite as a hydrophobic material, on binding capacity. The addition of both corrosion inhibitors (MCI and CNI) has minimal effect on the binding capacity, while the addition of Caltite reduces the binding capacity by limiting the contact of the samples with the salt in water due to its hydrophobic nature. In addition, the study compares the performance of the available fitting–binding models against the available experimental work in the literature, and shows that the Freundlich isotherm is the best fitting model for describing the relationship between the binding capacity and the free chloride. The study further relates the binding capacity to different compositions in cement and SCMs, and shows, by conducting quantitative analysis, that the Al2O3 content is the dominant factor affecting the binding capacity. Finally, this work proposes a new model, which uses Al2O3 content and free salt concentration to predict the bound chloride. The model shows adequate correlations to the experimental work and, further, can be used in service-life modeling of concrete

Modeling of Chloride Binding Capacity in Cementitious Matrices Including Supplementary Cementitious Materials

The improvement in the chloride binding capacity of concrete has been shown to increase corrosion resistance. The addition of supplementary cementitious materials (SCMs) to Portland cement has been proven to increase the binding capacity, except for silica fume, whereas the impact of chemical additives is not extensively addressed in the literature. This work studies the influence of SCMs and chemical additives, i.e., calcium nitrite inhibitor (CNI), migrating corrosion inhibitor (MCI), and Caltite as a hydrophobic material, on binding capacity. The addition of both corrosion inhibitors (MCI and CNI) has minimal effect on the binding capacity, while the addition of Caltite reduces the binding capacity by limiting the contact of the samples with the salt in water due to its hydrophobic nature. In addition, the study compares the performance of the available fitting–binding models against the available experimental work in the literature, and shows that the Freundlich isotherm is the best fitting model for describing the relationship between the binding capacity and the free chloride. The study further relates the binding capacity to different compositions in cement and SCMs, and shows, by conducting quantitative analysis, that the Al2O3 content is the dominant factor affecting the binding capacity. Finally, this work proposes a new model, which uses Al2O3 content and free salt concentration to predict the bound chloride. The model shows adequate correlations to the experimental work and, further, can be used in service-life modeling of concrete

Renewable Portfolio Standard Development Assessment in the Kingdom of Saudi Arabia from the Perspective of Policy Networks Theory

Electricity generation from renewable energy (RE) sources has not been well utilized in the Kingdom of Saudi Arabia (KSA). KSA has publicized its Vision 2030 renewable energy target to deploy 58.7 gigawatts of RE, paving the way for a low-carbon economy in the country. Renewable portfolio standard (RPS) may play an influential role as a policy instrument to stimulate the RE development and consumption on a large scale and pursue the Vision 2030 objectives. In this study, the renewable portfolio standards policy assessment was carried out to investigate the issues impelling the employment of or plan to adopt RPS. To elucidate the collaborating interaction amongst the multiple stakeholders at different levels in the formulation of renewable portfolio standard, in this assessment study, we used a multi-theoretical approach for examining the policy networks theory (PNT) to inspect the communication links and strategies of different actors who are responsible and involved in KSA policy formulation and enactment. It will help overcome the interaction limitations amongst the actors, contribute to understanding various actors’ behaviors and facilitate RPS development and implementation. In this paper, PNT’s four strategy phases (interaction, agenda-setting, action plan and legislative) are used for RPS development assessment. In this paper, we presented KSA’s overall systematic picture for RPS formulation to adopt and implement it practically for a collaborative relationship between five actors—policy and regulatory bodies, professional bodies, inter-governmental bodies, power producers and social networks—at different levels by using PNT to analyze the interactive relationship amongst actors. This detailed analysis will help KSA overcome the institutional relationship and interaction limitations of the actors in RPS formulation and thereby offer significant success for RE deployment in KSA, while providing viable ideas, procedures and bases for government departments to formulate applicable policies for the renewable energy system efficiently. The evaluation of the communications among major partakers in the policy network field helps to efficiently explicate the hindrances in policy formulation and enactment to make the RPS more effective