Renewable Energy Focus最新文献

In order to achieve the goal of carbon neutrality in the energy sector and promote sustainable economic development, it is critical to expand the depth of geothermal exploitation and accelerate the development of mid-deep geothermal energy. However, traditional hydrothermal geothermal systems are hindered by water scarcity, low heat extraction efficiency and so on. The solution may lie in using supercritical CO₂ (SCCO₂) instead of water for geothermal extraction, which not only enables efficient geothermal exploitation but also allows for additional CO₂ sequestration. This paper begins by introducing the current status and characteristics of geothermal resources, including hot dry rock, deep saline aquifers, and depleted oil–gas reservoirs, along with a review of related engineering cases in the world. Additionally, the advantages of SCCO₂ compared to water in heat extraction are examined, and progress in the development of CO₂ geothermal systems, CO₂-enhanced geothermal system (CO₂-EGS) and CO₂ plume geothermal system (CPGS), is summarized, highlighting the challenges they face. Furthermore, the paper explains the additional benefits of CO₂ geothermal systems. In the end, future research trends and development strategies are presented. For CO₂-EGS, reservoirs artificial fracturing technology should be the focus of future research. For CPGS, it is vital to improve the efficiency of heat extraction, with special attention given to the geothermal resources in depleted oil–gas reservoirs, particularly depleted gas reservoirs. The practical application of CO₂ geothermal systems requires the efforts of governments, research institutions, enterprises, and other stakeholders to work together.

Renewable energy sources are increasingly penetrating all power networks worldwide, despite the security status of these networks threatened by the fickle nature of these sources. Ninh Thuan Province (Vietnam) experienced a solar power boom in 2019–2021 and, with it, the congestion of both the local transmission and distribution networks. To solve congestions and operational security issues, large-scale storage solutions were considered and, due to land availability, Pumped Hydro Storage (PHS) technology was selected to solve these problems. However, the operational risks of cascade outage when integrating both renewables and a PHS system needs to be carefully considered, especially in a bulk power system. For this reason, this study examined the potential of integrating a large-scale grid-connected PHS system in ensuring operational security against the impacts of solar power plants in Ninh Thuan. The analyses of static and dynamic security were carried out for scenarios with and without the PHS system, including under current operational conditions. The results of the simulations show that the presence of the PHS improves both static and dynamic performance of the system, thus allowing full exploitation of solar power and avoiding curtailment. NEPLAN environment was chosen to simulate all scenarios under the Vietnamese grid code.

The proliferation of smart devices that complement the energy system in order to make it easier to change the appearance of unique and autonomous energy systems and make them more manageable, causes the biggest problems in energy management in smart cities. With these promising results, storing data exchange between the smart city and its components of renewable sources and storage will reduce the risk of cyber-attacks in the energy system. To solve these problems, this paper proposes a reliable and privacy-preserving distributed model for the transition to smart cities, emphasizing the integration of renewable energy sources such as wind, solar, and tidal power into the urban energy ecosystem. For this purpose, a distributed model-based two-dimensional multiplicative method (PDMM) and a design-based model have been developed as a fast method to solve energy problems in smart cities. The results will show that PDMM performs well in large-scale optimization problems. To protect data privacy, the method of secure data exchange is based on a modified acyclic graph based on blockchain. Detailed numerical results demonstrate the performance of the proposed method based on the dynamic force curve. The results prove that the proposed model was able to get to an optimal and true consensus among agents with very low error values.

This study investigates the utilization of renewable energy technologies, such as solar photovoltaics (PV) and energy storage, to reduce reliance on fossil-fuel microgrid generators in remote areas. However, renewable energy alone is not enough to address the existing challenges. Therefore, to optimize microgrid performance, it is crucial to incorporate shared energy storage and demand-response (DR) strategies from the demand side. Additionally, prosumers engaging in DR often encounter user-satisfaction issues. In this study, we propose a shared energy storage model that considers user satisfaction in remote areas. Additionally, we compared three energy storage models: individual, neighbor, and communal, to assess their effectiveness. To validate our findings, we juxtaposed two pricing scenarios: fixed and time-of-use (TOU) rates. The results of our study indicate that using shared energy storage leads to operational cost savings and increases user satisfaction compared to other scenarios. Finally, we employed the social index rate and performed a sensitivity analysis to determine the optimal operation that balances economic and environmental considerations.

The 21^st century’s booming population and escalating energy demands have driven significant efforts to enhance the Energy Hub (EH). The goal is to create a more intelligent and responsive system that can effectively cater to consumer needs while simultaneously improving the reliability and efficiency of contemporary energy infrastructure. The Internet of Things (IoT) has emerged as a key enabling technology for Smart Energy Hubs (SEH). While IoT offers a plethora of innovative solutions across various sectors, including critical infrastructure, it also introduces new security challenges. Since IoT devices inherently connect to the internet, SEH systems become susceptible to a wider range of cyberattacks. This vulnerability heightens as the number of integrated IoT devices increases. A single compromised device can expose the entire hub to cyber threats. Such attacks on energy sources have the potential to cripple entire cities, resulting in significant economic devastation. Therefore, robust security measures must be implemented before the widespread adoption of IoT-based devices in energy systems. This research delves into the architecture and infrastructure of IoT-enabled SEH. Following this, the focus shifts to analyzing the primary challenges and security concerns associated with their deployment. Finally, the research emphasizes cutting-edge approaches and tools that can bolster the security and resilience of IoT-enabled SEH against contemporary physical and cyber threats. Implementing secure and advanced data transmission systems based on blockchain technology holds promise in safeguarding the entire EH from cyber-physical attacks in the future.

Presently Rural Energy Communities (REC) are faced with challenges such as the inefficient distribution of energy from Renewable Energy Sources (RES), unfair pricing, and the inclusion of prosumers into the electricity market. Therefore, this article proposed an approach that employed enabling technologies such as Distributed Ledger Technologies (DLT), self-enforcing smart contracts-enabled Internet of Things (IoT), and Artificial Intelligence (AI) for sustainable energy sharing and tracking in REC. Additionally, a model is proposed based on key factors that influence the adoption of enabling technologies in REC. For the methodology qualitative data is collected from secondary sources and descriptive analysis is employed to present the key findings. Key findings from this study contributes to develop a decarbonized, decentralized, and digitized energy management approach to support the sustainability of REC. The deployment of AI can facilitate prediction short-term energy planning for RES production and consumption based on real-time data from IoT devices. More importantly, findings from this study presents use case scenarios of energy sharing and tracking, and green electric vehicle charging in REC suggesting that DLT based smart contracts, IoT, and AI offers an effective approach to accelerate the sharing and tracking of RES in REC. Besides, DLT and smart contracts enables real-time electricity consumption monitoring, energy trading management, and pricing.

Active Distribution Network shows promise in operating and controlling distributed generations. Based on ADN structural and electrical differences, ADN could be partitioned to reveal innate heterogeneity for better control. Virtual Microgrid works as such a partition mode that each VM serves both as a part of ADN and as an individual operating agent. To identify VM boundaries, previous research utilized community detection methods and then configured ADN based on stationary partition. In this paper, VM partition and configuration are simultaneously determined in the proposed Coupled-Configuration-Partition of Active Planning. Also, a new definition of electrical edge betweenness is proposed to depict interaction among power system buses to improve the partition algorithm. Based on this proposal, ADN is planned to be cohesive in Net-ability, Flexibility Supply Index, and Capacity Fitness, in the meantime to minimize the cost in a multi-objective optimization, iteratively in Genetic Algorithm to reach Pareto Front. Case studies are designed to denote the benefits of the proposed Coupled-Configuration-Partition of Active Planning in modularity and system cohesion intensity.