Energy Strategy Reviews最新文献

This study examines the impact of green economic growth and renewable energy on food security in Sub-Saharan Africa (SSA). The rationale for the study comes from the background that with a fast rate of growing population, there is a high pressure on natural resources, which often leads to resource depletion, being experienced across the globe. This study utilises panel data analysis consisting of 37 SSA countries that are members of the Official Development Assistance (ODA). Data was obtained from the Food and Agriculture Organisation (FAO) and World Development Indicators (WDI) for the period 2005–2022. To control for endogeneity, the study applies the system Generalised Method of Moments (GMM). The result shows that renewable energy and green economic growth have a positive significant impact on food security, though this impact is asymmetric across SSA sub-regions. On the other hand, industrialisation through its emissions, contributes negatively to food security. The implication is that SSA countries should focus on policies aimed at improving green economic growth and renewable energy consumption; while policies aimed at reducing the inefficient adoption of renewable electricity and discouraging industrialisation aimed at suppressing agricultural practices should be adopted.

Determining transportation routes is of great importance for advancing China-Russian gas cooperation, which has been hanging in the balance. This paper employs a general equilibrium model to assess the congestion cost of diversified gas transmission schemes between China and Russia on domestic long-distance pipelines, which addresses the inherent limitations of exclusively considering transport impacts in the decision-making process. Findings reveal a notable decrease in pipeline congestion incidents for the route integrated with the Shaan-Jing system, thus lending empirical credence to the feasibility of the proposed scenario involving Mongolia. In addition, key routes are defined in this paper based on congestion costs, which emphasize the challenges posed by bilateral gas cooperation to China's long-distance natural gas pipeline network, necessitating a strategic focus on critical pipelines as the top priority of pipeline optimization efforts in the future. This paper provides valuable insights into planning the second China-Russia gas pipeline and the decision-making process for the future development of long-distance pipeline infrastructure.

Studying the interplay between energy imports and employment is paramount for attaining sustainable development in Germany. The research employs the time-varying parameters-vector autoregression-stochastic volatility (TVP-VAR-SV) methodology to capture the dynamic correlation between energy import price (EIP) and unemployment rate (UR) under the control of consumer price index (CPI), which is constantly evolving. In quantitative analyses, it is clear that EIP significantly and positively impacts UR, indicating that a surge in imported energy costs has adverse consequences for the German labour market, possibly leading to job cuts and a spike in unemployment. Conversely, UR has a notable negative impact on EIP, particularly in the short period, signifying that an elevated unemployment rate reduces demand for imported energy. Further, the favourable impact of EIP on CPI, coupled with CPI's detrimental effect on UR, underscores the pivotal importance of CPI as a critical control variable. Additionally, we reinforce the robustness of these conclusions through stringent testing that encompassed the introduction of a business cycle-related control variable, variations in the number of iterations and replacement of energy import price. Amidst the severe energy crisis, this study aims to offer crucial recommendations to Germany for securing its energy imports and stabilising the labour market.

This paper explores the intricate interplay of socio-economic drivers influencing environmental sustainability in oil-importing countries, examining CO₂ emissions and greenhouse gas concentrations over the period from 2000 to 2021. Employing the Feasible Generalized Least Squares (FGLS) and Prais-Winsten regression method (PCSE), data from fifteen major oil-importing nations are scrutinized. The study identifies pivotal socio-economic factors, including environmental innovations, green energy adoption, and energy prices, as key drivers in mitigating emissions. Environmental innovations, catalyzing cleaner technologies, emerge as effective tools in curbing hazardous emissions and promoting green energy sources. The study underscores the trade-off between energy use and prices, advocating a strategic shift towards green energy adoption. It also highlights the adverse association between industrial and agricultural production with emissions. Policy interventions are recommended, emphasizing the need for cleaner technologies and the adoption of renewable energy practices, thus achieving a harmonious balance between economic development and environmental quality. The research offers valuable insights into the socio-economic dimensions of environmental sustainability, emphasizing the importance of well-balanced policies that align environmental innovations, environmental conservation, and energy transition in oil-importing nations within the broader context of human-environment interactions.

Europe has recently experienced an energy crisis that began with the war between Russia and Ukraine and continued with reciprocal sanctions and power cuts, increasing geopolitical tensions and risks. In such an environment, European countries must decide how to replace energy imports from Russia. As the best option may be to rely on clean energy, this study explores how geopolitical risk (GPR) affects clean electricity generation (i.e., hydro, solar, wind, & nuclear) in five European countries (i.e., Bulgaria, Czechia, Germany, Romania, and Switzerland), which have a high dependency on Russia. The study therefore uses daily data between January 2, 2019 and January 29, 2024 and applies a set of nonlinear methods (i.e., wavelet coherence, quantile-on-quantile regression, Granger causality in quantiles, and quantile regression). The results show that (i) there is a strong dependence of GPR on renewable and nuclear electricity generation over different times, frequencies, and countries; (ii) GPR stimulates hydro electricity generation at higher quantiles across countries except the Czechia; (iii) GPR increases solar electricity generation at higher quantiles in all countries except the Czechia and Switzerland; (iv) GPR mainly stimulates wind electricity generation at higher quantiles, except for Bulgaria and Switzerland; (v) GPR is almost inefficient in nuclear electricity generation. Overall, the study clearly shows the supportive effect of the GPR in promoting renewables, while this is not the case for nuclear energy. Therefore, European countries can rely on renewables as the best alternative against energy blackouts in the short term, considering the varying effect based on time, frequency, quantile, country, and clean energy sources.

Establishing a sustainable industrial structure system is imperative for transforming the society to high-quality development and achieve the "carbon peak" and "carbon neutrality" goals. In this study, we explored a low-carbon pathway of regional industrial structure optimization to achieve a balance among economic growth, social security, and environmental conservation. A multi-objective optimization model of industrial structure of economic-social-environmental system was constructed by minimizing carbon emissions and maximizing economic benefits and social employment. In this study, we explored the scientific allocation path for industrial structure and set various scenarios to meet the diverse preferences and development requirements of decision-makers. Southwest China was used as a practical case to validate the model's efficacy, offering a decision-making framework for the sustainable development of the regional economy. After optimization, carbon emissions reduced by 0.9 %∼3.2 %, economic benefits increased by 2.5 %∼4.8 %, and employment levels nearly doubled. The proportion of the transportation industry in southwest China decreased by 11.58 %. The raw coal was the energy source with the highest contribution to carbon emissions, 2494.2 × 10⁸ $kgC{O}_{2}eq$.

Bangladesh launched the Vision 2021 initiative to reach the status of a middle-income country and provide universal access to power. This gave an impetus to a significant rise in installed generation capacity, with the most positive developments seen through the Seventh Five-Year Plan and beyond. The purpose of this case study is to conduct a systematic review of Bangladeshi power sector performance after independence, from 1972 through post-2000, including the Sixth and Seventh Five-Year Plans with their notable reforms, sector unbundling, potential concerns, and realistic adjustments related to developmental targets. This study adopted a qualitative research design comprising semi-structured interviews and archival data. The results reveal that the Vision 2021 initiative was instrumental in ensuring universal access to power. It was also revealed that there is no predetermined process to achieve the desired power sector outcome, as a successful outcome is dependent on contextual factors, complementary and targeted policies, and alternative institutional pathways to achieve the best sector performance outcomes. Despite significant achievements in raising the installed generation capacity in the power sector, serious operational deficits and structural weaknesses remain. These are (i) the increased cost of electricity production, and (ii) continuing operational deficits in the power sector. Some revisions have been suggested for the long-term sustainability of this sector. This study is the first of its kind to systematically analyze Bangladesh's power sector performance from post-independence through post-2000 to 2024.

A growing number of public and private energy buyers are interested in 24/7 carbon-free energy (CFE) procurement, which means that every kilowatt-hour of electricity consumption is met by carbon-free sources at all times. It has the potential to overcome the limitations of established procurement schemes, such as the temporal mismatch between clean electricity supply and buyers’ demand that is inherent to “volumetric” matching. Yet it is unclear how 24/7 CFE procurement affects the rest of the power system, and whether this effect is consistent across regional contexts and different levels of system cleanness. We use a mathematical model to systematically examine different designs, optimal procurement strategies, costs, and impacts of the 24/7 CFE matching, both for participating buyers and for regions where voluntary procurement occurs. We examine mechanisms driving system-level emissions reduction and how they vary across regions and over time. Our results indicate that clean energy procurement commitments have consistent beneficial effects on participants and the electricity system. Utilising an hourly matching strategy, energy buyers can eliminate all carbon emissions linked to their electricity consumption, while also reducing system-level emissions by up to 572 kgCO${}_2$/a per MWh of participating load. Even as grids become cleaner over time, the hourly matching strategy contributes significantly to system-level emissions reduction. In addition, voluntary commitments to 24/7 CFE have a further transformative effect on electricity systems through accelerated innovation and early deployment of advanced energy technologies.

A potential solution to improve electricity access is to provide rural communities with a stable and resilient electric power supply from reliable and sustainable energy sources. Considering resilience in rural electrification planning can bring about longer techno-economic viability of rural power supply projects. For this purpose, this paper introduces ResQ-RDSS, a Resilience Quantification-based Regional Decision Support System. The novelty of ResQ-RDSS is integrating resilience quantification, optimization, and multi-hazard risk assessment into multi-criteria decision-making. The ResQ-RDSS aims to formulate a resilient electrification solution most suitable for each village to enhance the availability of electricity access for rural communities. ResQ-RDSS comprises four modules: Spatial Techno-Economic Assessment (STEA), Earthquake-induced Risk Assessment (ERA), Flood-induced Risk Assessment (FRA), and Decision Maker (DM). The STEA module considers six geospatial criteria to appraise the techno-economic suitability of villages for installing off-grid solar PV systems. This module classifies rural communities according to their suitability. The ERA and FRA modules quantify the resilience of the rural power transmission network to earthquake and flood scenarios, respectively, and classify the rural communities into two groups using multi-hazard disaster resilience metrics and decision-making parameters defined for the probabilistic resilience assessment. Finally, the DM module facilitates the selection of a resilient electrification strategy, installing off-grid PV systems or connecting to the power grid, for each rural community in the region of interest. The 158 rural settlements in Birjand County, Iran, exposed to earthquake and flood risks were selected for a case study to demonstrate the ResQ-RDSS's ability to help devise resilient regional electrification strategies. In this case study, the suitability of villages for installing solar PV systems and the resilience of rural power supply against natural hazards were evaluated and accordingly, possible resilient solutions for electrifying each village were compared and selected. The STEA, ERA, and FRA modules, respectively, classify 38, 53, and 55 villages (out of 158) for off-grid solar PV installation. Depending on the strategy selected by the decision-maker, ResQ-RDSS identifies between 13.3 % and 48.1 % of villages in the case study as suitable for deploying off-grid PV systems. The resilient electrification strategy can be selected by considering various factors, including budget constraints, stakeholders' interests, the local conditions of rural areas, policymakers' opinions, regional hazard risk assessment reports, and future development plans.