This research paper conducts an extensive exploration of onshore, offshore, and floating offshore wind turbines, pivotal components in the landscape of sustainable energy generation. The study thoroughly investigates various wind energy systems, shedding light on their distinct attributes, advantages, and limitations. The examination of onshore wind turbines encompasses aspects such as installation procedures, size considerations, wind dynamics, accessibility challenges, and visual impact assessments. Similarly, the analysis of offshore wind turbines covers considerations such as location selection, installation complexities, size variations, wind conditions, environmental impacts, and visual aesthetics. The paper also delves into the emerging technology of floating offshore wind turbines, highlighting their unique features, advantages, and technological advancements. A thorough comparative examination is conducted to assess the economic, environmental, and social aspects of onshore, offshore, and floating offshore wind turbines. The research paper concludes by offering insights into policy considerations, addressing research gaps, and outlining prospects for the seamless integration and advancement of these diverse wind energy systems. This comprehensive review aspires to contribute to the existing knowledge base in sustainable energy generation, fostering informed decision-making for a greener and more sustainable future.

Nowadays, electricity theft is a major issue in many countries and poses a significant financial loss for global power utilities. Conventional Electricity Theft Detection (ETD) models face challenges such as the curse of dimensionality and highly imbalanced electricity consumption data distribution. To overcome these problems, a hybrid system Multi-Layer Perceptron (MLP) approach with Gated Recurrent Units (GRU) is proposed in this work. The proposed hybrid system is applied to analyze and solve electricity theft using data from the Chinese National Grid Corporation (CNGC). In the proposed hybrid system, first, preprocess the data; second, balance the data using the k-means Synthetic Minority Oversampling Technique (SMOTE) technique; third, apply the GTU model to the extracted purified data; fourth, apply the MLP model to the extracted purified data; and finally, evaluate the performance of the proposed system using different performance measures such as graphical analysis and a statistical test. To verify the consistency of our proposed hybrid system, we use three different ratios for training and testing the dataset. The outcomes show that the proposed hybrid system for ETD is highly accurate and efficient compared to the other models like Alexnet, GRU, Bidirectional Gated Recurrent Unit (BGRU) and Recurrent Neural Network (RNN).

Purpose – The purpose of this paper is to evaluate the economic impact of an oil and gas company's maintenance management ineffectiveness and identify its causes. Design/methodology/approach – The method followed in this paper consists of the examination of official documents, the observation of operations at the oil and gas company and interviews with company employees. For that purpose, a questionnaire was prepared and used to detect dysfunctions in the existing maintenance system. A statistical tool was also used to evaluate the degree of conformity between the maintenance system and maintenance management effectiveness according to various factors. Findings – Maintenance management ineffectiveness generates a significant financial loss for the company. Research limitations/implications – This paper does not examine the impact of maintenance management ineffectiveness on safety, health and the environment. For reasons of confidentiality, the company name is not mentioned. Practical implications – This paper presents an evaluation of the financial losses caused by maintenance management ineffectiveness, findings which may prove useful to top management. In another way, this paper demonstrates that significant financial profit can be made by improving maintenance performance. Furthermore, system maintenance auditing may be extended to the company's other plants and subsidiaries using the methods presented in this paper. The results of these audits can be generalized usefully such as to be used as a guide to outline plans for improving maintenance performance in the company. Originality/value – This paper evaluates the impact of maintenance management ineffectiveness in order to convince top management of the necessity of being involved in the process of maintenance improvement.

Climate change is mostly caused by the production of electricity, which makes environmentally friendly energy solutions like floating solar photovoltaic (PV) systems necessary. The efficiency, cost-effectiveness, and environmental impact of ground-mounted, floating, and agrivoltaic PV systems are all thoroughly assessed and contrasted in this study. The benefits of installing PV systems on bodies of water, which can maximize land usage and improve energy output, are a major area of focus. The study also explores agrivoltaics, a potential strategy that tackles the problem of land use disputes by fusing solar power generation with agricultural practices. Performance comparisons, a thorough economic and environmental assessment, and a full analysis of agrivoltaic trials are all included in this paper. Additionally, it looks at how PV systems deteriorate and how to identify failures, offering preventative and remedial measures based on international research. The paper provides recommendations for improving the design, deployment, and long-term sustainability of PV plants, especially those that incorporate agrivoltaic systems, with an emphasis on current performance data and degradation trends. The findings aim to lead the future development of more efficient and environmentally friendly solar energy technologies.

The increasing expansion of the industrial and domestic sectors, combined with the integration of renewable energy sources, has led to an overload of the existing interconnected power systems, which in turn has led to significant bottlenecks. This confluence of factors manifests itself in severe frequency, voltage and tie-line power issues, highlighting the urgent need for intelligent control mechanisms. Automatic voltage regulation (AVR) and load frequency control (LFC) are key components that ensure the supply of high-quality energy to consumers while maintaining the nominal frequency, voltage and power deviations in the grid. These measures are essential to ensure the stability and safety of the IPS under these challenging conditions. This research addresses the control strategies for a four-area sophisticated IPS. The complexity of the system, which includes five generation units in each area, including gas, thermal reheating, hydropower and two renewable energy sources (wind and photovoltaic), requires a careful study of the control methods. In particular, the inclusion of various non-linear factors, such as the governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics (BD) in each of the four areas, increases the realism of the study. In this context, a recently introduced meta-heuristic algorithm, the One-to-One-based Optimizer (OOBO), was used to determine the optimal parameters of the proportional-integral-proportional-derivative (PI-PD) controller. The tuning process involves using the integral of time multiplied by the squared error value (ITSE) as the error criterion for evaluating the fitness function. In the study, the voltage, frequency and power performance of the OOBO PI-PD controller is evaluated and compared with alternative control methods, namely Proportional-Integral-Derivative (PID), Integral-Proportional (I-P) and Integral-Proportional-Derivative (I-PD) controllers, all of which are tuned with OOBO. Under the influence of a 5% load step load perturbation (SLP), comprehensive comparisons show the superior performance of the OOBO PI-PD controller, which shows better responses in all areas. Furthermore, the reliability and effectiveness of the OOBO PI-PD method are validated by a sensitivity analysis that considers simultaneous variations of the turbine time constant and speed control within a range of ±25%. The results highlight the robustness of the OOBO-PI-PD control strategy and demonstrate its ability to effectively stabilize variations in terminal voltage, load frequency and tie-line power with a significantly shorter settling time within the complicated dynamics of a four-area IPS with nonlinearities.