Special Issue on Advances in Maintenance Management

1. Introduction

This book covers research relating to advanced analytics in renewable energy and shows how to apply these analytics to many different professional areas, including engineering and management. Each chapter of this book is contributed by different authors from across the world and covers a different area of analytics and its application to renewable energy. The book connects analytical principles with business practices and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management in renewable energy. It also refers to other disciplines such as economics, finance, marketing, behavioural economics, and risk analysis. This book is of particular interest to researchers, engineers and economists who are developing new advances in analytics but also to practitioners working on these subjects.

2. Power Converter of Electric Machines, Renewable Energy Systems, and Transportation

Maintenance is a critical industry aspect that is required to achieve competitiveness, and is one of the most important industry aspects, along with operations, in the energy industry. Therefore, correct management of the corrective, predictive, and preventive maintenance in any energy industry is required. This book, “Advances in Maintenance Management”, considers the main concepts, state-of-the-art advances and case studies relating to this topic.

This book covers original research works with content that is complementary to other sub-disciplines in maintenance management such as economics, finance, marketing, decision and risk analysis, engineering, etc.

The book also considers real case studies, including important topics such as failure detection and diagnosis, fault trees, and subdisciplines (e.g., FMECA, FMEA, etc.) [1]. It is essential to link these topics with financial, schedule, resources, downtimes, etc., to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime in the energy industry [2].

Advances in mathematics, models, computational techniques, and dynamic analysis are employed in maintenance management, where this book presents the most important contributions. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support analysis of multi-criteria decision-making problems with defined constraints and requirements are also presented.

The work presented in Ref. [3] is mapped to scrutinize the consequence of biodiesel and gaseous fuel properties, and their impact on compression-ignition (CI) engine combustion and emission characteristics in single- and dual-fuel operation. Biodiesel prepared from non-edible oil source derived from Thevetia peruviana belonging to the plant family of Apocynaceaeis. The fuel has been referred to as methyl ester of Thevetia peruviana (METP) and adopted as pilot fuel for the effective combustion of compressed gaseous fuel of hydrogen. This investigation is an effort to augment the engine performance of a biodiesel-gaseous-fuelled diesel engine operating under varied engine parameters. Subsequently, consequences of gas flow rate, injection timing, gas entry type, and manifold gas injection on the modified dual-fuel engine using conventional mechanical fuel injections (CMFIS) for optimum engine performance were investigated. Fuel consumption, CO, UHC, and smoke formations are found to be lower, in addition to higher NOx emissions compared to CMFIS operation. The fuel-burning features such as ignition delay, burning interval, and variation of pressure and heat release rates with crank angle are scrutinized and compared with base fuel. Sustained research in this direction can convey practical engine technology, concerning fuel combinations in the dual-fuel mode, paving the way to alternatives which counter the continued use of fossil fuels, which has detrimental impacts on the climate.

Maintenance management is a key pillar in companies, especially energy utilities which have high investments in assets. Therefore, for proper maintenance management, the process has to be integrated and aligned with other departments in order to conserve asset value and guarantee services. In this line, Intelligent Assets Management Platforms (IAMP) are defined as software platforms to collect and analyze data from industrial assets. They are based on the use of digital technologies in industry. In addition to the fact that the practise of monitoring and managing assets over the Internet is growing in relevance, Ref. [4] states that the IAMPs should also support a much more balanced and more strategic view of existing asset management and proper maintenance management. Real transformation can be achieved if these platforms help to understand business priorities in work and investments. In Ref. [4], first discussed are the factors explaining IAMP growth. Next is explained the importance of considering, well in advance, those managerial aspects of the problem, for proper investments and suitable digital transformation through the adoption and use of IAMPs. A case study in the energy sector is presented to map or to identify those platform modules and apps providing important value-added features to existing asset management practices. Attention is also paid to the methodology used to develop the apps’ data models from a maintenance point of view. To illustrate this point, a methodology for the development of the asset criticality analysis process data model is proposed. Finally, the paper includes conclusions of the work and literature relevant to this research.

A condition-based maintenance policy for offshore wind turbines is presented in consideration of the maintenance uncertainty and the weather effect in Ref. [5]. In this paper, the offshore wind turbine is divided into four main assemblies—the rotor, gearbox, generator, and pitch system. The support vector machine classification technique is implemented to analyze the failure information, which was collected from field data in China. According to the results of fault diagnosis and prediction, the assembly that reaches the corresponding maintenance threshold will be repaired. At the same time, a maintenance opportunity occurs for the rest of the components, and an optimized plan can be determined by arranging the maintenance combination and time. The calculated results indicate that the proposed condition-based maintenance policy is beneficial to reduce the maintenance expenditure of offshore wind turbines.

Ref. [6] analyses the impact of the operation and maintenance procedures on the condition of gearbox oil. The analytical results reveal how different scenarios modify the outcome. The analysis is based on key operational data collected from 30 different multi-megawatt wind turbines at different locations in Spain with a variety of technologies from different top-tier manufacturers. The study includes various situations and decisions—such as leakage and replacement of oil, offline filter installation, oil brand change, substitution of valves, and even the position where the sample is taken—and how these situations can provoke false warnings that trigger modifications in the operation and maintenance of wind farms with new and unnecessary tasks and costs. The experimental results conclude that complete and reliable information is crucial when producing warnings relating to risk situations. It is not possible to take appropriate action without accurate information and, consequently, the spread of the problem cannot be stopped.

To improve the trackability of in-wheel motor drive (IWMD) and wheel-individual steer electric vehicles (EVs) when steering actuators fail, the fail-operation control strategy was proposed Ref. [7] to correct vehicles in a steering failure situation and to avoid losing control of vehicle steering. A linear quadratic regulator (LQR) decides the additional yaw moment of the vehicle according to vehicle state errors. The tire force estimation module estimates the compensating resistance moment generated by the failed wheel according to the tire slip angle and the vertical tire force. By isolating the failed wheel, the optimal torque distribution (OTD) controller allocates the additional yaw moment and the compensating resistance moment to normal wheels to realize the fail-operation control of the IWMD vehicle. The control effect was verified through co-simulation of MATLAB/Simulink and Trucksim. Compared with the uncontrolled and direct torque allocation methods, when failure occurs, the proposed OTD method reduces the lateral trajectory error of the vehicle by 86% and 60.5%, respectively, and demonstrates a superior ability to maintain velocity, which proves the effectiveness of the proposed fail-operation control strategy.

Yearly generation maintenance scheduling (GMS) of generation units is important in each system, for example, in combined heat and power (CHP)-based systems, in order to decrease sudden failures and premature degradation of units. Imposing repair costs and reliability deterioration of system are the consequences of ignoring the GMS program. In this regard, Ref. [8] accomplishes GMS inside CHP-based systems in order to determine the optimal intervals for predetermined maintenance required duration of CHPs and other units. In this paper, cost minimization is targeted, and the violation of units’ technical constraints, such as feasible operation region of CHPs and power/heat demand balances, are avoided by considering related constraints. Demand–response-based short-term generation scheduling is accomplished in this paper, taking into account the maintenance intervals obtained in the long-term plan. Numerical simulation is performed and discussed in detail to evaluate the application of the suggested mixed-integer quadratic programming model that was implemented in the General Algebraic Modeling System software package for optimization. Numerical simulation is performed to justify the model’s effectiveness. The results reveal that long-term maintenance scheduling considerably impacts short-term generation scheduling and total operation cost. Additionally, it is found that the demand response is effective from the cost perspective and changes the generation schedule.

In recent decades, power generation using wind has exhibited a vast scope of extensive utilization and capacity add-on worldwide. The use of wind power has increased and become a great source of renewable power production. In the latter decades of the 20th century, the installed capacity of wind energy almost doubled every three years. Ref. [9] presents and reviews the crucial facets of wind power, along with the developing strategies that have been approved and adopted by the Indian government for intensifying the country’s power security, especially in terms of the appropriate usage of existing power sources. From India’s perspective, wind energy is not only utilized for power production but also to provide power by more economical means. The particulars of India’s total energy production, contributions of numerous renewable-sources and their demand are also encompassed in this paper. The current scenario of wind power production of India is also paralleled with that of other prominent countries globally.

3. Future Works

Despite the closure of this Special Issue, a thorough investigation on the issues related to maintenance management is expected in the near future. Thereby, achievements relating to advances in maintenance management pose ongoing challenges to the research community.