This study analyses the potential of renewable energy to reduce inflationary pressures arising from energy imports in Turkiye. Annual data for the period 1980-2022 are used in the analysis. In this study, unit root properties are examined using the Zivot-Andrews and Lee-Strazicich tests, both of which explicitly account for structural breaks. Cointegration is investigated via the Johansen and Hatemi-J cointegration tests. Long-run coefficients are subsequently estimated using the DOLS and FMOLS estimators. The robustness of the empirical findings is further assessed using the ARDL approach. In addition, an interaction term is constructed to measure the impact of renewable energy in alleviating inflationary pressures arising from energy imports. The results show that energy imports and exchange rate have an increasing impact on inflation, while renewable energy and the interaction term have a decreasing impact. DOLS, FMOLS, and ARDL results support each other. Moreover, in both models, the impact of renewable energy in mitigating inflationary pressures stemming from energy imports is stronger than the direct disinflationary impact of renewable energy.
The transition to electric vehicles (EVs) is driven by the need to reduce emissions and dependency on fossil fuels, with propulsion systems at the heart of the transformation. However, the adoption of EVs may be challenged by a variety of significant issues, like inadequate charging infrastructure, battery constraints, charging speed, cost, energy density, and dependency on crucial elements such as cobalt and lithium. EV expansion and widespread adoption stimulate power electronic converter and control research to develop reliable, low-cost, and high-power battery charging solutions. In this paper, an in-depth review is carried out on various scientific aspects pertaining to the control methods of power converters for EV chargers available in the literature. First, the current and future global status of the EVs and charger market is provided along with a comprehensive classification of various types of EVs and EV chargers. Then, control strategies for front-stage AC/DC converters along with isolated and non-isolated DC-DC Converters focusing on objectives, features, control parameters, designs, and the latest advancements are thoroughly reviewed and compared. After that, a detailed comparison is provided between commercially available On-board and Off-board EV chargers on the basis of output current and voltage, power, operating temperature, weight, length, compatible protocols, price, and output efficiency. Next, a case study that compares the complete design and simulation results of a 1 kW On-board charger and a 90 kW Off-board charger in Matlab/Simulink is presented. Finally, the conclusion includes a concise recommendation for further work, current advancements, and future roadmaps.
Kirsten Franzen, Alice Favero, Caleb Milliken
et al.
ABSTRACT As global interest in enhancing energy security, reducing energy costs, and promoting rural economic development grows, the use of forest residues for bioenergy has gained attention. While bioenergy derived from forest residues can help meet power needs and support policy goals, significant uncertainty remains regarding the greenhouse gas (GHG) emissions associated with their production and use. This study aims to explore the key drivers of these uncertainties by reviewing estimates of GHG emissions from forest residue use for energy, as presented in peer‐reviewed journals, reports, and gray literature. The findings reveal a wide range of GHG emission outcomes, with some studies suggesting net emissions and others indicating net removals. This uncertainty stems from the complexity of time scales, variety of forest management approaches and feedstock quality, assumptions about alternative scenarios, and varying approaches to emissions accounting. Recognizing that each method has its unique attributes, we propose an ideal framework that integrates multiple approaches to provide a more comprehensive assessment of the potential net GHG outcomes of using forest residues for energy.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
Power-to-Gas (P2G) technologies gain recognition for enabling the integration of intermittent renewables, such as wind and solar, into electricity grids. However, determining the most cost-effective operation of these systems is complex due to the volatile nature of renewable energy, electricity prices, and loads. Additionally, P2G systems are less efficient in converting and storing energy compared to battery energy storage systems (BESs), and the benefits of converting electricity into gas are not immediately apparent. Deep Reinforcement Learning (DRL) has shown promise in managing the operation of energy systems amidst these uncertainties. Yet, DRL techniques face difficulties with the delayed reward characteristic of P2G system operation. Previous research has mostly focused on short-term studies that look at the energy conversion process, neglecting the long-term storage capabilities of P2G. This study presents a new method by thoroughly examining how DRL can be applied to the economic operation of P2G systems, in combination with BESs and gas turbines, over extended periods. Through three progressively more complex case studies, we assess the performance of DRL algorithms, specifically Deep Q-Networks and Proximal Policy Optimization, and introduce modifications to enhance their effectiveness. These modifications include integrating forecasts, implementing penalties on the reward function, and applying strategic cost calculations, all aimed at addressing the issue of delayed rewards. Our findings indicate that while DRL initially struggles with the complex decision-making required for P2G system operation, the adjustments we propose significantly improve its capability to devise cost-effective operation strategies, thereby unlocking the potential for long-term energy storage in P2G technologies.
The massive integration of uncertain distributed renewable energy resources into power systems raises power imbalance concerns. Peer-to-peer (P2P) energy trading provides a promising way to balance the prosumers' volatile energy power generation and demands locally. Particularly, to protect the privacy of prosumers, distributed P2P energy trading is broadly advocated. However, severe privacy leakage issues can emerge in the realistic fully distributed P2P energy trading paradigm. Meanwhile, in this paradigm, two-party and multi-party computations coexist, challenging the naive privacy-preserving techniques. To tackle privacy leakage issues arising from the fully distributed P2P energy trading, this paper proposes a privacy-preserving approach via hybrid secure computations. A secure multi-party computation mechanism consisting of offline and online phases is developed to ensure the security of shared data by leveraging the tailored secret sharing method. In addition, the Paillier encryption method based on the Chinese Remainder Theorem is proposed for both the secure two-party computation and the offline phase of the multi-party computation. The random encryption coefficient is designed to enhance the security of the two-party computation and simultaneously guarantee the convergence of the distributed optimization. The feasible range for the encryption coefficient is derived with a strict mathematical proof. Numerical simulations demonstrate the exactness, effectiveness, and scalability of the proposed privacy-preserving approach.
The European Union aims to achieve climate-neutrality by 2050, with interim 2030 targets including 55% greenhouse gas emissions reduction compared to 1990 levels, 10 Mt p.a. of a domestic green H2 production, and 50 Mt p.a. of domestic CO2 injection capacity. To support these targets, Projects of Common and Mutual Interest (PCI-PMI) - large infrastructure projects for electricity, hydrogen and CO2 transport, and storage - have been identified by the European Commission. This study focuses on PCI-PMI projects related to hydrogen and carbon value chains, assessing their long-term system value and the impact of pipeline delays and shifting policy targets using the sector-coupled energy system model PyPSA-Eur. Our study shows that PCI-PMI projects enable a more cost-effective transition to a net-zero energy system compared to scenarios without any pipeline expansion. Hydrogen pipelines help distribute affordable green hydrogen from renewable-rich regions in the north and southwest to high-demand areas in central Europe, while CO2 pipelines link major industrial emitters with offshore storage sites. Although these projects are not essential in 2030, they begin to significantly reduce annual system costs by more than EUR 26 billion from 2040 onward. Delaying implementation beyond 2040 could increase system costs by up to EUR 24.2 billion per year, depending on the extent of additional infrastructure development. Moreover, our results show that PCI-PMI projects reduce the need for excess wind and solar capacity and lower reliance on individual CO2 removal technologies, such as Direct Air Capture, by 13 to 136 Mt annually, depending on the build-out scenario.
Abstract Layered metal oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical specific capacity and wide Na+ diffusion channels. However, the irreversible phase transitions and cationic/anionic redoxes cause fast capacity decay. Herein, P2-type Na0.67Mg0.1Mn0.8Fe0.1O2 (NMMF-1) cathode material with moderate active Fe3+ doping has been designed for sodium storage. Uneven Mn3+/Mn4+distribution is observed in NMMF-1 and the introduction of Fe3+ is beneficial for reducing the Mn3+ contents both at the surface and in the bulk to alleviate the Jahn–Teller effect. The moderate Fe3+/Fe4+ redox can realize the best tradeoff between capacity and cyclability. Therefore, the NMMF-1 demonstrates a high capacity (174.7 mAh g−1 at 20 mA g−1) and improved cyclability (78.5% over 100 cycles) in a wide-voltage range of 1.5–4.5 V (vs. Na+/Na). In-situ X-ray diffraction reveals a complete solid-solution reaction with a small volume change of 1.7% during charge/discharge processes and the charge compensation is disclosed in detail. This study will provide new insights into designing high-capacity and stable layered oxide cathode materials for SIBs.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Today, most hydrogen production is based on natural gas and occurs locally at the demand sites. However, according to many studies, hydrogen generation will shift to greenhouse gas (GHG)-neutral sources and supply, substantially increasing demands to meet ambitious climate protection targets in the European Union. Therefore, the model-based analysis in this paper addresses where hydrogen will come from in a GHG-neutral target system. A scenario study examines different expansion paths of renewable energy generation technologies and variations in European cooperation regarding energy trading. The model results show that a domestic European hydrogen supply strategy is cost-efficient. This result is robust even with higher self-sufficiency shares of individual countries. However, delayed or restricted expansions of renewable electricity generation technologies lead to increased hydrogen demands for power generation and increased pipeline-bound hydrogen imports in winter from the Middle East and North Africa in the model results. Furthermore, scenarios with higher photovoltaic shares exhibit increased demand for hydrogen storage for seasonal energy supply and demand balancing and increased hydrogen demands for power generation. A cost-efficient hydrogen supply strategy should, therefore, particularly focus on the expansion of onshore wind energy and hydrogen supply technologies in Europe and strengthen European cooperation for energy supply infrastructures.
Precise value of scheduling decisions forms the cornerstone of water distribution network (WDN) scheduling optimization, which aims at conserving energy and enhancing network operational efficiency. This article proposes a computational methodology for evaluating the value chain of scheduling decisions in WDN. The scheduling process is modeled as a Markov decision process with immediate reward function, action and state space. Due to the periodicity of water supply and sequential nature of scheduling, the calculation quantifies cumulative value of scheduling decisions by incorporating state transition probability with expected value. The effectiveness and applicability of the proposed evaluation method are demonstrated using scheduling data from a real world WDN. The method provides rational values on scheduling period and strategies, offering practical feedback for scheduling decisions.
River, lake, and water-supply engineering (General), Water supply for domestic and industrial purposes
Renewable energy promotes the sustainable development of the environmental protection industry (EPI) and the economy. Meanwhile, the EPI provides various technologies and services for renewable energy, which is an important guarantee for the renewable energy market. This paper combines the DY and BK spillover indexes to discuss the cross-market risk contagion effect between EPI and renewable energy market from the perspective of time-frequency spillover. The results show that: (1) The spillover effect between the EPI and renewable energy market is cyclical from the perspective of frequency domain, and the total market spillover is dominated by high-frequency spillover. And the risk contagion has the characteristics of time-varying and vulnerability from the perspective of time domain. (2) The net spillover effect shows that the EPI plays the role of a net exporter in different frequency domains, the solar energy and the hydro market play more roles as risk receivers, and the role of the wind energy market is frequently converted. (3) The risk spillover network structure shows that EPI acts as an important node in the cross-market risk contagion path. Driven by EPI, the short-term risk transmission follows the path of “EPI-biomass energy-other four renewable energy markets”, and the medium and long-term follows the path of “EPI-wind energy-other four renewable energy markets”.
The Pierre Auger Observatory, the world's largest observatory of ultra-high-energy cosmic rays (UHECR), offers a unique insight into the properties of hadronic interactions occurring in air showers at energies well above those reached at human-made accelerators. The key probe into the hadronic interactions has, for a long time, been the number of muons arriving at the ground, which can be directly measured at Auger for energies up to 10 EeV using dedicated underground muon detectors or estimated through the observation of highly inclined showers using the surface detector of the Observatory. Further information can be obtained using the hybrid character of the Observatory, which allows the simultaneous observation of the longitudinal development of the shower with the fluorescence (and lately also radio) detector and the ground signal with the surface detector. Several different analyses using hybrid data show a discrepancy between the predictions of simulations based on the latest hadronic interaction models and data. This discrepancy has been long interpreted as a deficit in the number of muons predicted by the simulations with respect to the data. A new analysis using a global fit of the data on selected hybrid showers has shown that the disagreement between models and data is more complex and also involves the predictions for the depths of the maxima of the longitudinal shower development. At the same time, measurements of shower-to-shower fluctuations using inclined hybrid events show good agreement with the predictions, suggesting that the observed muon discrepancy is rather the result of a gradual accumulation of small changes during the shower development than of a major change in the properties of the first interaction. Recently, the Observatory has undergone an upgrade, which includes several components aimed at a significant improvement ...
Abstract Background The need to balance renewable energy supply with biodiversity conservation has become increasingly urgent in light of current climate, energy, and biodiversity crises. However, the development of wind and solar energy often presents trade-offs such as competing for land use and potentially impacting species and habitats. To address these concerns, ‘priority zones’ for bird and bat species have been proposed as spatial designations for early species protection in the regional planning process. However, there are concerns that the areas suitable for wind and solar energy may be limited further, making it difficult to meet state- and regional-specific spatial targets for renewable energy sites. Results To help decision-makers deal with this challenge, a Multi-Criteria Scenario Framework has been developed and analyzed. It involves a habitat model of priority zones for species conservation and techniques from the intuitive logic scenario planning method. Through a regional case study, various planning criteria were analyzed according to scenarios, such as priority zones for species protection, settlement buffers, and forests. The framework indicates how criteria could be balanced to achieve wind energy spatial targets as well as targets for ground-mounted solar energy with the least possible impact. Results show that compared to other planning criteria, species priority zones had limited competition with spatial wind energy targets. Achieving these targets may require minimal adjustments, such as allowing wind energy in 1–3% of completely protected recreational landscapes. To reconcile land use demands in the energy transition, a balance between ‘green’ protected areas is necessary. Additionally, ground-mounted solar energy could replace some of the wind energy spatial targets while also meeting the overall solar development goals. Conclusions The framework provides transparency in assessing trade-offs between multiple objectives and helps quantify the ‘costs’ and ‘benefits’ in renewable energy planning. Adapting more flexible planning methods could help resolve the conflict between wind energy and species protection. Joint analysis of the areas needed for wind and solar energy and determining the optimal energy mix are gaining in importance. However, how the benefits of multi-criteria scenarios can be achieved within the confines of preoccupied and siloed organizations remains an ongoing research topic.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
This paper presents a detailed validation of a modeling framework and its implementation for the simulation of flame spray pyrolysis (FSP) using different nozzle geometries of the so-called SpraySyn burner. Gas, liquid and particulate dynamics are compared against experimental data from literature as well as our own laser-Doppler anemometry, phase-Doppler anemometry and multi-line OH laser-induced fluorescence thermometry imaging measurements. The modeling framework consists of large eddy simulations (LES) coupled to the sparse-Lagrangian multiple mapping conditioning (MMC) model, a Lagrangian spray solver and a sectional description of the population balance equation. Simulations start downstream of the burner exit planes where turbulent inlet data for the gas and liquid phases are generated by independent LES that use a 1-Fluid method to capture the dynamics of the liquid jet break-up. The gas and liquid dynamics are validated and analyzed for an ethanol spray flame in the SpraySyn1 and SpraySyn2 burners. In these burners iron(III) oxide particulates are synthesized from iron pentacarbonyl (IPC)-ethanol solutions with varying IPC concentrations. The results demonstrate the very good predictive capabilities of the MMC modeling framework for the gas and liquid phases. The predictions of the particulate formation are validated by comparison of elastic light scattering (ELS) signals from experiments against synthetic ELS signals calculated from the simulations. Results are of reasonable accuracy for the SpraySyn1 FSP series but indicate an imbalance between particulate growth and dilution with the surrounding gas. Predictions for the SpraySyn2 FSP series are consistent with SpraySyn1 results and indicate an increased product particulate size due to an increased residence time downstream of the heat release zone.
Fuel, Energy industries. Energy policy. Fuel trade
Abstract Background The paper aims to elucidate to what extent the German Parliament exerts control over rail planning. Parliament has the budgetary right, but information asymmetries vis-à-vis the railway company Deutsche Bahn and the Ministry of Transport make parliamentary control difficult. Methods Recently, Germany has instituted a parliamentary review process that allows the Parliament to take up concerns by the public affected by rail projects. We use the principal-agent theory to model this new institution. Parliament delegates rail planning to the Deutsche Bahn, while the Federal Railway Authority serves as a budget watchdog, and parliament uses input from public participation as a deck-stacking procedure. The paper first situates the institutional innovations—the new parliamentary oversight procedure—against the former logic of railway planning. Second, based on the documentation of parliamentary oversight, we analyze for which demands by the affected public the Parliament uses its power to change rail projects. Results The paper showed that public participation matters. The German Parliament introduced expensive changes to rail projects. In particular, demands that had been voiced in well-institutionalized public participation (that is, when municipalities, regional associations, etc., were engaged in long-term institutionalized dialogues with the Deutsche Bahn) were more likely to be addressed. An Extra budget was then allocated to, for example, noise-regulating measures. Conclusions To sum up, the German Parliament uses information gained in public participation in combination with its budget rights to exert control over railway planning for conflictual projects. Thus, Parliament takes a more active role in railway planning. Whether this also leads to more acceptance for rail projects, is an open question.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
We develop a cosmological theory in which the evolution of the universe is controlled by the cosmological constant and dominated by the associated vacuum energy. The universe starts as a classical de Sitter space with an infinite effective vacuum energy density, which decreases subsequently like 1/t^3. The corresponding Friedmann-Robertson-Walker (FRW) scale factor also decreases over time, showing that the common assumption that it describes the expansion of the universe is incorrect and should be abandoned. Instead, the (cubic) expansion of the universe is needed to satisfy energy conservation. Once the vacuum energy density has decreased to the Planck level the first elementary particles can be created through a direct conversion of vacuum energy. After this epoch, the enormous kinetic energy enables a quick magnification of the number of particles through ordinary production processes in tandem with the expansion of space. The dominance of vacuum (dark) energy is supposed to persist into later epochs, which enables a perturbative treatment of matter and radiation leading to linear equations, which replace the usual FRW equations. The presence of matter changes the vacuum metric, inducing a secondary matter term which might explain the phenomenon of dark matter. Together with a similar induced radiation term, it provides a possible explanation for the recent acceleration of the expansion of the universe. The theory unifies particle physics and cosmology by expressing particle physics units in terms of the gravitational and cosmological constant. This relationship also explains a number of numerical coincidences which have long puzzled physicists.
ABSTRACT Australia is a well-known climate laggard with a history of political conflict over climate policy and the dubious distinction of being the only country to repeal a national emissions trading scheme (ETS). This article examines the puzzle of why four subnational governments in Australia’s federation succeeded in enacting durable framework climate legislation based on a model that came to be widely regarded as ‘best-practice’. We show that in 2007 South Australia was the first jurisdiction in the world to enact framework climate legislation with a 2050 emissions reduction target and an independent expert advisory committee to provide guidance on the implementation of interim targets. We show that this local legislative innovation set off a process of political learning, policy transfer and a virtuous political competition among like-minded Labour and Labour-Green governments at the subnational level. We call this ‘convergent evolution’ insofar as the legislative innovation and diffusion over the period 2007–2015 was similar to, but occurred independently of, the UK Climate Change Act 2008 and the diffusion of this model elsewhere in Europe. Common to all cases was a strong commitment by the premier and/or the relevant minister to pursue a decarbonisation strategy via targets, and reliance on sources of advice for legislative reform that were professionally and/or politically committed to climate action rather than from vested industry groups. More generally, we argue that framework climate legislation carries lower political risks than an ETS because it does not draw attention to the upfront costs of action. The diffusion of subnational climate change legislation, accompanied by renewable energy promotion, has helped to limit the impacts of Australian national climate policy failure while also providing a springboard for renewed climate legislative momentum at the national level. Key Policy Insights Similar innovations in climate policy and legislation can occur independently in different regions in response to similar global pressures. Framework climate legislation based on long-term and progressive interim targets carries lower political risks than an ETS because it does not draw as much attention to the upfront costs of action. Innovation in subnational framework climate legislation in a federation can generate a virtuous competition in target setting and renewable energy promotion in states that are not heavily dependent on fossil fuels or close to retiring fossil fuel assets.
Increasing electric vehicles (EV) penetration leads to significant challenges in EV battery disposal. Reusing retired batteries in distributed energy systems (DES) offers resource-circular solutions. We propose an optimisation framework to model the emerging supply chains and design strategies for reusing the retired EV batteries in DES. Coupling a supply chain profit-allocation model with a DES design optimisation model, the framework maximises the whole chain profit and enables fair profit distribution between three interactive sectors, i.e., EV, DES, dismantling and recycle (D&R) sectors. Our research highlights the system implications of retired batteries on DES design and new modelling insights into incentive policy effectiveness. Our case study suggests significant potential value chain profits (2.65 million US$) achieved by deploying 10.7 MWh of retired batteries in the DES application with optimal retired battery price of 138 US$/kWh. The revenue support on D&R sector is suggested as a promising incentive scheme than tariff support.