A paradigm shift in power systems is observed due to the massive integration of renewable energy sources (RESs) as distributed generators. Mainly, solar photovoltaic (PV) panels and wind generators are extensively integrated with the modern power system to facilitate green efforts in the electrical energy sector. However, integrating these RESs destabilizes the frequency of the modern power system. Hitherto, the frequency control has not drawn sufficient attention due to the reduced inertia and complex control of power electronic converters associated with renewable energy conversion systems. Thus, this article provides a critical summary on the frequency control of solar PV and wind-integrated systems. The frequency control issues with advanced techniques, including inertia emulation, de-loading, and grid-forming, are summarized. Moreover, several cutting-edge devices in frequency control are outlined. The advantages and disadvantages of different approaches to control the frequency of high-level RESs integrated systems are well documented. The possible improvements of existing approaches are outlined. The key research areas are identified, and future research directions are mentioned so that cutting-edge technologies can be adopted, making the review article unique compared to the existing reviews. The article could be an excellent foundation and guidance for industry personnel, researchers, and academicians.

To operate photovoltaic (PV) systems efficiently, the maximum available power should always be extracted. However, due to rapidly varying environmental conditions such as irradiation, temperature, and shading, determining the maximum available power is a time-varying problem. To extract the maximum available power and track the optimal power point under these varying environmental conditions, maximum power point tracking (MPPT) techniques are proposed. The application of MPPT for extracting maximum power plays a crucial role in developing efficient PV systems. These MPPT techniques face several issues and limitations, particularly during partial shading conditions caused by non-uniform environmental conditions. Researchers have been focusing more on mitigating the partial shading condition in PV systems for the last few years due to the need to improve power output and efficiency. This paper provides an overview of MPPTs proposed in the literature for uniform and non-uniform environmental conditions broadly categorized as MPPT-based and circuit-based methods. The MPPT-based methods are classified as conventional, soft computing, and hybrid techniques. A critical analysis of each approach regarding tracking speed, algorithm complexity, and dynamic tracking under partial shading is discussed. The literature shows hybrid strategies provide fast-tracking speed and are efficient with a tracking efficiency of around 99% compared to conventional methods; however, their design and practical implementation are complex. This comprehensive review of MPPT methods aims to provide power utilities and researchers with a reference and guideline to select the best MPPT method for normal operation and partially shaded PV systems based on their effectiveness and economic feasibility.

Over the last few years, the electric energy demand in the Kingdom of Saudi Arabia (KSA) has increased many folds due to several factors including increased population, industrialization, economic activities, and urbanization. The main source of electric power generation in KSA is the burning of petroleum products. Almost one third of greenhouse gas (GHG) emissions are contributed from the electric power generation sector, mainly, by burning diesel and natural gas. As a result, it makes it necessary to consider alternate forms of electricity generation in order to cut down emissions and to keep sustainable growth alive. The government has planned to diversify energy sources and suppliers. In recent years, energy generation from renewable sources including solar photovoltaic (PV), wind, concentrated solar power (CSP), biomass, geothermal, and tidal, has been given more importance. The ambitious Saudi Vision 2030 targets of 58.7 GW of power generation from renewable energy sources will cause a significant reduction in GHG emissions from the energy sector. This article systematically reviews the impact of renewable energy generation on GHG emissions. The detailed breakdown of GHG emission is discussed. Then, the status of renewable energy generation is investigated, focusing on the technical and economic potentials. The correlation of renewable energy generation and GHG emissions is then explained. The most distinguishing feature of this review is that it provides a comprehensive list of recommendations to reduce GHG emissions. The discussions and recommendations of this article will support decision makers, system planners, industry personnel, researchers, and academics to develop sustainable energy pathways for the Kingdom.

The Southeast Asian region has been eagerly exploring the concepts of smart city initiatives in recent years due to the enormous opportunities and potential. The initiatives are in line with their plan to promote energy efficiency, phase down/out fossil fuel-based generation, and reduce greenhouse gas emission intensity and electrification of various sectors in addition to renewable energy targets and policies to achieve net zero emissions by 2050 or 2060. However, the major challenges for these countries are related to leadership, governance, citizen support, investment, human capacity, smart device heterogeneity, and efficient modeling and management of resources, especially the energy systems. An intelligent energy system is one of the most significant components for any functional smart city, where artificial intelligence (AI), the internet of things (IoT), and big data are expected to tackle various existing and evolving challenges. This article starts with a brief discussion of smart city concepts and implementation challenges. Then, it identifies different types of smart city initiatives in Southeast Asian countries focusing on energy systems. In addition, the article investigates the status of smart systems in energy generation and storage, infrastructure, and model development. It identifies the unique challenges of these countries in implementing smart energy systems. It critically reviews many available energy modeling approaches and addresses their limitations and strengths, focusing on the region. Moreover, it also provides a preliminary framework for a successful energy system that exploits AI, IoT, and big data. Finally, the roadmap for a successful energy system requires appropriate policy development, innovative technological solutions, human capacity building, and enhancement of the effectiveness of current energy systems.

Experts have been searching for ways to mitigate the impacts of climate change on resources since the early 20th century. In response, the World Economic Forum introduced the concept of a “nexus”, which involves the simultaneous, systematic collaboration of multiple individuals or sectors, such as water, energy, and food, in order to create an integrated approach to reducing resource scarcity through a multi-disciplinary framework. In contrast, a circular economy (CE) involves restructuring material flows from a linear economic system and closing the loop on resource exploitation. Both the nexus and CE have been developed to address the overexploitation of resources, but they also contribute to the Sustainable Development Goals (SDGs) and decouple carbon emissions from economic growth. This study explores the potential of combining the nexus and CE to pursue the SDGs on a global scale. Our findings reveal significant research gaps and policy implementation challenges in developing countries, as well as the potential consequences of adopting integrative scenarios. Finally, we propose a system dynamics model as a way to address the difficulties of coupling policies and to better understand the interdependencies between different parts of the economy.

Renewable energy will play a vital role in greenhouse gas emissions reduction. However, renewable energy is located far away from the load center. Modular multilevel converter-(MMC) based VSC-HVDC systems became competitive for remotely located renewable energy grid integration. Unlike the average model for MMC and renewable energy side converter, this paper presents a detailed model-based control and analysis of the MMC-HVDC system for solar and wind energy integration. Furthermore, it optimally tracks PV energy employing the modified incremental conductance method and wind energy using field-oriented control. Instead of decoupled control, a feedforward controller is utilized to establish a standalone AC voltage for renewable energy grid integration. This work considers a doubly fed induction generator (DFIG), permanent magnet synchronous generator (PMSG), and squirrel cage induction generator (SCIG) for wind energy integration. The results from MATLAB/SIMULINK platform agree with the controller hardware in the loop results from RTDS-dSPACE platform. The results confirmed the optimum solar and wind energy tracking during wind speed, irradiance, and temperature variations. However, it improved the fault ride-through capability during balanced and unbalanced low voltage disturbances at the point of common coupling (PCC) of AC grid.