Energy Strategy Reviews最新文献

Given the scarcity of freshwater resources, the growing significance of desalination is undeniable. It holds immense potential, particularly in regions grappling with severe water shortages. However, desalination's Achilles heel lies in its voracious energy appetite, requiring roughly ten times more energy than wastewater treatment. Moreover, the prevalent use of fossil fuels in desalination plants poses concerning issues like environmental pollution, fossil fuel depletion, and rising costs. The present study has designed an integrated Water desalination and treatment Network that includes a number of desalination facilities, storage centers, wind farms, and wastewater treatment facilities. The water desalination and treatment network has been structured using a Mixed-Integer Linear Programming (MILP) model, considering uncertainties in wind power and water demand. Employing a chance constraint probabilistic programming approach, this model ensures robustness and balances conservatism with investment attractiveness. It aims to enhance resilience against fluctuations in wind energy and water demand within the water and energy supply chain network. The study applied this model to optimize the locations of desalination plants, treatment centers, and storage facilities. This integrated model ensures autonomy, eliminating the need for external water and energy sources while reliably meeting regional demands. In the context of the Makran coasts case study, our comprehensive mathematical model demonstrates an optimal allocation with 96.67 % attributed to fixed costs and only 3.33 % to variable costs. Moreover, this model precisely optimizes the locations of two desalination centers, two storage facilities, and ten water treatment centers, effectively managing the need for external water resources. Ultimately, through a rigorous sensitivity analysis, we unveiled that the chance constraint parameters have a significant impact on the variable costs.

The proliferation of environmental pollutants, the financial implications of energy transmission and distribution, the scale of electrical network assets, and the accessibility and finite nature of fossil fuels collectively constitute significant catalysts for the progression of renewable energies. Within this framework, the present study scrutinizes governmental performance in mitigating energy poverty and investigates the pragmatic implementation and economic viability of harnessing solar energy and compact wind turbines to provide electricity to two distinct, remote, and underprivileged regions of Iran. These regions have persistently confronted the predicament of energy inaccessibility, rendering the establishment of conventional infrastructure financially burdensome. The study contemplates three scenarios: the integration of solar panels and batteries, the combination of wind turbines and batteries, and standalone wind turbines. The Loss of Power Supply Probability (LPSP) is incorporated to augment system reliability, thereby elucidating its influence on costs. This study employs a diesel generator as a cost-efficient contingency measure to scrutinize system reliability under conditions where LPSP ≠ 0. The precision of the results procured is corroborated using mathematical optimization functions in the linear Simplex model for the first and third scenarios, and the nonlinear model with the genetic algorithm for the second scenario. The findings disclose that in both regions, the scenario involving small wind turbines and batteries emerges as the most optimal, with costs amounting to 9600$ for the case 1 and 6420$ for the case 2, culminating in a substantial reduction in energy supply costs relative to other scenarios. This underscores the advantageous impact of cultivating renewable energies in areas with high potential. Moreover, the non-economic costs associated with the establishment of a traditional electricity distribution network, which will be 27 times higher for the first village and 49.8 times higher for the second village compared to the optimal scenario (wind turbine and battery), have been demonstrated.

Consequently, the outcomes of this study, which underscore the optimality of small wind turbines at low and stable wind speeds, aid decision-makers in implementing cost-effective strategies for alleviating long-term energy poverty and fostering the development of energy, health, communication, and education systems.

Many countries proposed their ambitious climate change targets to address the global warming challenge through accelerating the pace of energy transition towards renewable energy. However, such transition will increase the demand for critical minerals. This paper conducts a thorough bibliometric review of the related literature to offer a holistic understanding on such challenges. First, the definition of climate change target, energy transition and critical mineral are clarified. Second, a systematic bibliometric search and analysis are conducted to identify research trends. It revealed that the number of related publications has grown significantly over the past decade. Then, the most productive countries, institutions, authors, main academic disciplines, the most popular methods and the energy sectors that are most focused in this field are identified. Results show that the entire energy system, wind and solar renewable energies were the most focused energy technologies. Stock-driven Material Flow Analysis (MFA) emerges as the main methodology employed. China and Chinese authors were the most productive in this field. In addition, the hot topics and future directions of publications were identified through dividing keywords into climate change, mineral, and energy. Finally, a mineral-energy-climate knowledge framework is constructed to illustrate the linkage between mineral constraints, climate change and energy transition.

China's energy transition is a pivotal component of global efforts to combat climate change. This study identifies the synergistic effects of key factors driving this transition, including social-technology-economic, policy, investment, governance indicators. Asymmetric nexus impacts are explored by using quantile-on-quantile regression (QQR) method. Further, the synergistic effects of key drivers on China's energy transition are examined by model 1–4. The findings show that reconciling the tradeoffs of reducing coal emissions and promoting clean energy are crucial for China's energy transition. Urban growth, environmental taxes, financial development, and strong environmental governance and institutional quality significantly support these efforts, but show different synergistic effects scenarios. These findings also reinforce the need for a more inclusive response to China's energy sustainability challenges, in particular, coordinated policies and strategies in coal-reliant industrial sectors are critical for a successful energy transition.

This study analyzes the determinants of green economic growth in OECD countries, focusing on the role of technological innovation, clean energy adoption, environmental innovation, and political stability. Employing panel data analysis techniques, including Dynamic Seemingly Unrelated Regression (DSUR), Common Correlated Effects Pooled-FM (CUP-FM), and Common Correlated Effects Pooled-BC (CUP-BC), the study examines the asymmetric relationships between these factors and green growth over both the short and long run. The findings suggest that technological innovation significantly influences green growth in OECD nations, with positive and negative shocks in innovation showing distinct impacts on green growth consumption, which emphasizes embracing and expanding green technology to enhance sustainable economic development and minimize environmental damage. Similarly, clean energy adoption plays a crucial role in fostering green economic growth, with positive relationships observed between renewable energy consumption and green growth in the short and long run. Environmental innovation also positively correlates with green growth, highlighting the significance of developing new products and services to manage environmental challenges. Besides, political stability is a critical determinant of green growth, with stable political environments fostering investor confidence and encouraging long-term sustainable investments. The study underlines the complex interplay between these factors, emphasizing the bidirectional causality relationships observed among clean energy adoption, political stability, innovation, and urbanization. These findings underscore the multifaceted nature of sustainable development pathways, highlighting the need for integrated policy approaches to promote green growth agendas. The study contributes to comprehending the factors driving green economic growth in OECD countries and provides insights for policymakers and practitioners seeking to advance sustainability goals. By underlining the importance of technological innovation, clean energy adoption, environmental innovation, and political stability, the study proposes valuable insights into the pathways toward achieving environmentally sustainable and economically viable growth.