Renewable Energy Research Articles

The Eectricity Crisis and the Feasibility of Nuclear Energy in Egypt

The power outage crisis is increasing in Egypt, negatively affecting many other sectors such as industry, agriculture, and trade. In light of the lack of sufficient capacity to meet the growing needs of consumers, which has led to regular power shortages and power outages. While Egypt needs additional energy, the production of gas and oil needed to generate thermal energy decreased in 2014, and Egypt moved from an exporter of natural gas to a net importer. In addition to this, the volume of subsidies allocated to energy increased, the rise in global prices for oil and natural gas, and the need for huge investments to create Power generation plants, development of transportation networks, and distribution of electrical energy, which led to pressure on the general budget. A continuous and reliable supply of electricity is needed for Egypt's social and economic development. Accordingly, the government encouraged the development of new energy, invited the private sector to participate in energy generation, and a number of government reforms were made in order to enhance competition in the energy market, which required the need to study the possibility of providing it using nuclear energy. Its stations have a high load capacity, operate almost at full capacity all the time, are characterized by the stability of the electrical network and energy independence, and avoid the risks of fuel price shocks, and the costs of generating electricity from them decrease with increasing production. The importance of this research lies in highlighting the challenges facing the structure of the electricity sector in Egypt, and studying the advantages enjoyed by nuclear energy as the most important renewable energy sources in the world. Its importance also lies in comparing nuclear energy with other energy sources, and trying to benefit Egypt from obtaining this energy for use. In economic development projects, rationalizing tariffs and supporting their access to the poor. <i>This research is divided into</i>:<i>The first topic</i>: The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution, <i>The second topic</i>: trends in development planning for establishing nuclear plants in Egypt. The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution.

Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems

The urgent need to mitigate climate change and reduce reliance on fossil fuels has driven the global shift towards renewable energy sources (RESs). However, the intermittent nature of RESs poses significant challenges to the widespread adoption of Zero-Carbon Smart Grids (ZCSGs). This study proposes a synergistic framework to address this hurdle. It utilizes energy storage systems (ESSs) by comparing Vanadium redox flow batteries (VRFBs) and Lithium ion batteries (LIBs) to identify the most suitable option for ZCSGs, with precise models enabling robust performance evaluation. Moreover, an accurate demand-side management (DSM) strategy considering power elasticity to manage discrepancies between electricity load, RES generation, and ESS availability is introduced for estimating fair, dynamic tariffs. An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. Simulations demonstrate significant reductions in carbon footprint, peak power demand, and reliance on fossil fuels. The study finds that VRFBs outperform LIBs in cost and security, and dynamic tariffs based on accurate DSM significantly reduce energy costs. This work explores the challenges and opportunities of this integrated approach, offering policy recommendations and future research directions for truly optimized ZCSG implementation.

Uncovering Displacement between Nuclear and Renewable Electricity Generation for G7 Countries by Novel Wavelet-Based Methods

ABSTRACT Under the pressure of climate-related issues, importance of clean electricity generation (EG) has been developing in ensuring sustainable environment. Accordingly, countries have been trying to increase clean EG. Although increasing clean EG is important, it is also critical that clean EG alternatives should not cause displacement. Otherwise, there may not be certain progress in stimulating clean EG. So, this study aims to investigate displacement between nuclear and renewable EG types. In this context, the study considers four clean EG sources (i.e. nuclear, hydro, solar, and wind), analyzes G7 countries, uses high-frequency daily data between 1 January 2019 to 30 December 2023, applies novel Wavelet Local Multiple Correlation (WLMC) method as the main model, and performs Wavelet Transform Coherence (WTC) for the robustness check. The study defines that (i) hydro and wind EG have a displacement (supporting) effect on nuclear EG at short (long) term; (ii) solar EG has a supporting (displacement) effect on nuclear EG at short (long) term; (iii) the most critical EG source is nuclear for France and United States and hydro for Great Britain and Japan; (iv) the WTC method reveals the robustness. The study determines that renewable EG has a displacement (supporting) effect on nuclear EG in short (long) term. Therefore, there are certain conflict between nuclear and renewable EG in the short term, whereas they support each other in the long term. Thus, there is a need for comprehensive and balanced energy transition policy so that choices should not cause a displacement among alternatives.

Promoting real-time electricity tariffs for more demand response from German households: a review of four policy options

Abstract Background Demand response is an important option for accommodating growing shares of renewable electricity, and therefore, crucial for the success of the energy transition in Germany and elsewhere. In conjunction with smart meters, real-time (or ‘dynamic’) electricity tariffs can facilitate the flexibilization of power consumption and reduce energy bills. Whilst such tariffs are already quite common in several EU member states, Germany lags behind in this respect. The country makes for an interesting case study because of the sheer volume of additional flexibility that its energy transition necessitates. Main text This paper discusses how German policymakers can make real-time tariffs more attractive for households and thus entice them to better adapt their consumption to current market conditions. Following an analysis of the current impediments to the adoption of such tariffs, we discuss four policy options: (1) a more ambitious legal definition of real-time tariffs that can promote market transparency and leverage potential savings for consumers, (2) a shift in energy taxation that encourages the uptake of renewable power and increases price spreads, (3) a new model of dynamic network charges which combines grid-serving and market-serving incentives, and (4) a subsidy for users of real-time tariffs that helps internalise the benefits they provide to all electricity consumers. Given the similar regulatory framework, our suggestions should generally also apply to other countries in Europe and beyond. Conclusions Overall, we argue that there is considerable scope for policymakers to better exploit market forces to ensure security of electricity supply at lower social cost. Our call for stricter regulation in order to allow the markets to better guide consumer behaviour may seem like a paradox—but it is one well worth embracing.

A refined method for optimising inverter loading ratio in utility-scale photovoltaic power plant

This paper proposes a novel approach for designing the inverter loading ratio (ILR) for utility-scale PV systems. As the first of its kind, a deterministic approach is proposed for dealing with such a design issue. The design objective is to maximise the economic reliability of the photovoltaic (PV) Plants. The problem is reformulated using a linear programming (LP) technique. The proposed solution allows dealing with each system individually and requires only the information of the DC/AC power conversion unit system. The results are tailored for utility-scale PV systems but can also be easily revamped for residential and private/industrial installations. The results were validated using a real-world case study of a utility-scale PV power plant in Ireland, operating under the Renewable Electricity Support Scheme (REFIT) feed-in tariff. These results were compared with the design method from the commercial PVsys software. In the proposed case study, reducing the ILR value from 1.4656 (as designed by PVsys) to 1.4528 led to an increase in annual profit annuities, demonstrating the effectiveness of the proposed approach.

Regional Framework Towards Establishing Treatment, Storage, and Disposal (TSD) Facilities for PV Waste Management in the Philippines: A Case Study of Laguna Province

Abstract. The accelerated adoption of photovoltaic (PV) systems for renewable power generation in the Philippines will yield a tremendous amount of PV waste. However, the country lacks a comprehensive framework for understanding PV module waste volume growth and optimally siting Treatment, Storage, and Disposal (TSD) facilities for PV waste management based on minimum siting factor. The study aims to develop a regional framework that utilizes a geographic information system (GIS)-based approach to find the potential sites and optimal locations of TSD facilities in Laguna, Philippines, based on the estimated PV module waste growth of solar energy systems with service contracts and minimum siting criteria under Department of Environment and Natural Resources (DENR) Administrative Order 2013-22. By 2060, the projected amount of PV module waste in Laguna province will be around 162,230 metric tons based on the waste projection results. The suitable sites cover around 19,720.5 hectares or 11.21% of the total land area of Laguna, which were determined by various siting factors that encompass social, economic, and environmental factors and obtained using binary suitability analysis and vector overlay analysis. The optimal locations of the two TSD facilities were identified using strategic positioning based on hotspot analysis, clustering algorithm, and proximity analysis. Consequently, the distance and GHG emissions of the two optimal locations were calculated. Indeed, the approach will serve as a guide for policymakers and other stakeholders in understanding PV module waste growth and strategically and optimally position TSD facilities on suitable sites for efficient and effective PV waste management.

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

Mitigating Risk and Emissions in Power Systems: A Two-Stage Robust Dispatch Model with Carbon Trading

The large-scale integration of renewable energy sources is crucial for reducing carbon emissions. Integrating carbon trading mechanisms into electricity markets can further maximize this potential. However, the inherent uncertainty in renewable power generation poses significant challenges to effective decarbonization, renewable energy accommodation, and the security and cost efficiency of power system operations. In response to these challenges, this paper proposes a two-stage robust power dispatch model that incorporates carbon trading. This model is designed to minimize system operating costs, risk costs, and carbon trading costs while fully accounting for uncertainties in renewable energy output and the effects of carbon trading mechanisms. This model is solved using the column-and-constraint generation algorithm. Validation of an improved IEEE 39-bus system demonstrates its effectiveness, ensuring that dispatch decisions are both robust and cost-efficient. Compared to traditional dispatch models, the proposed model significantly reduces system risk costs, enhances the utilization of renewable energy, and, through the introduction of a ladder carbon trading mechanism, achieves substantial reductions in carbon emissions during system operation.

Assessing the role of circular economy and green innovation in mitigating carbon emissions in the Visegrad countries

The shift towards a circular economy is an essential measure in achieving sustainable development because it seeks to separate economic expansion from resource use and environmental deterioration. To meet the European Union green deal, waste management, and the net zero emissions targets various countries are developing and adopting prudent strategies. This study investigates the dynamic affiliation between circular economy (CIR), green innovation (INV), renewable energy (REE), economic progress (GDP), and urbanisation (URB) on carbon emissions (CO2) in the Visegrad (V4) countries, comprising the Czech Republic, Hungary, Poland, and Slovakia. Using the CS-ARDL technique and quantile regression, data curation from 1990-2022 was analysed after checking for cross-sectional, unit root, and cointegration. The outcome demonstrates that circular economy, green innovation, and renewable energy had a negative effect on carbon emissions. In addition, GDP and URB had an immaterially positive influence on carbon emissions. Lastly, the quantile regression confirmed that the study provides useful information for policymakers and stakeholders in the Visegrad countries. It emphasised how important it is to take a broad approach to circular economy initiatives, support eco-friendly innovations, carry out renewable energy projects, and manage the urbanisation process well to achieve long-term economic growth and environmental health.

Latent Information in the Evolving Energy Structure

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) and Triple-Difference (DDD) models to investigate the effects of AI. The research initially demonstrates that AI may exhibit dual attributes of constraining energy structure. Specifically, the rapid development of AI tends to increase the proportion of fossil fuel-based electricity generation while optimizing the consumption of renewable energy. Furthermore, the degradation of energy structure stems from the surge in electricity consumption by AI, which the renewable energy consumption capacity is unable to satisfy. Lastly, industrial agglomeration effects and the construction of the digital economy have positive impacts on development of renewable energy; technological innovation aids in mitigating the negative shocks to the energy structure. This study provides a new perspective on the role of AI technology in energy transition.

Numerical Study on Combustion Characteristics of a 600 MW Boiler Under Low-Load Conditions

Under the background of achieving carbon dioxide peaking and carbon neutrality, the rapid development of renewable energy power generation poses new challenges to the flexible adjustment capabilities of traditional power plants. To explore the furnace combustion stability and optimal operation modes during deep peak shaving, a simulation of the combustion process under low-load conditions for a 600 MW wall-fired boiler is performed utilizing computational fluid dynamics (CFD) analysis. The impact of burner combination modes on the combustion process within the furnace is explored at 25% and 35% boiler maximum continuous ratings (BMCRs). This study investigates two configurations of burner combinations. One mode operates burners in layers A, B, and C, which include the lower layers of burners on the front and rear walls of the boiler, as well as the middle-layer burners on the rear wall, referred to as OM1. The other mode operates burners in layers A and C, which include the lower layers of burners on the front and rear walls of the boiler, referred to as OM2. The results indicate that OM2 exhibits superior capabilities in orchestrating the distribution of the airflow velocity field and temperature field under the premise of ensuring no more than a 1% decrease in the pulverized coal burnout rate. When OM1 is employed, the airflow ejected from the middle-level burners hinders the upward movement of pulverized coal sprayed from the lower-level burners, causing a larger proportion of pulverized coal to enter the ash hopper for combustion. Consequently, the ash hopper attains a peak mole fraction of CO2 at 0.163. OM2 delays the blending of pulverized coal with air by enhancing the injection quantity of pulverized coal per burner. As a result, the generation of CO in the ash hopper reaches a notable mole fraction of up to 0.108. The decreased furnace temperature promotes the formation of fuel-based NOx during low-load operation. Taking the 25% BMCR as an example, the NOx emissions measured at the furnace outlet are 743 and 1083 ppm for OM1 and OM2, respectively. This study focuses on the impact of combustion combinations on the combustion stability when the boiler is operating at low loads. The findings could enrich previous research on combustion stability and contribute to the optimization of combustion schemes for power plant boilers operating at low loads.

Comparative Approaches to Energy Transition: Policy Guideline for Enhancing Thailand’s Path to a Low-Carbon Economy

Thailand’s transition to a low-carbon economy faces significant challenges, including a dependency on fossil fuels, fluctuating energy costs, and limited policy clarity. This study conducts a comparative analysis of energy transition policies in Germany, Japan, Australia, Malaysia, and Singapore to derive actionable lessons that can be adapted to Thailand’s socio-economic and energy contexts. Using the Integrated National Energy Planning (INEP) framework and Network Governance Theory, the research identifies key strategies, such as setting clear and achievable renewable energy targets, establishing robust legal frameworks, fostering multi-stakeholder engagement, and encouraging decentralized governance. The findings highlight the importance of long-term vision, inclusive governance, and targeted investments in renewable technologies to accelerate energy transitions. This paper presents policy guidelines to enhance Thailand’s energy security and contribute to its climate goals by promoting public awareness and strengthening institutional capacities. By adapting these strategies, Thailand can align with global energy trends, reduce its reliance on fossil fuels, and advance toward a resilient and sustainable energy system, aligned with global energy trends while addressing its unique socio-economic context.

Optimal Planning of Standalone Rural Microgrid With Effective Dispatch Strategies and Battery Technology

ABSTRACTMicrogrids are a viable substitute for traditional power systems because they may deliver cleaner, more dependable, affordable power with fewer losses. However, the microgrid's performance is impacted by the variable nature of renewable energy sources. Battery storage is a crucial component of microgrid planning since it defines the system's techno‐economic feasibility. A standalone rural microgrid is designed in the current study, employing three distinct battery types: lithium‐ion, lead acid, and zinc‐bromine flow. The suggested microgrid's techno‐economic analysis employs three distinct dispatch mechanisms, that is, cycle charging, load flow, and complete dispatch. The case study of the suggested framework is carried out in Lucknow (India). The system comprises PV/battery/wind energy system/diesel and battery. The simulation results suggest that the optimal system with the least electrification cost is 0.113 $/kWh using complete dispatch strategies and a zinc‐bromine battery. It has 206 kWh zinc‐bromine flow batteries, a 10 kW converter, a 20 kW PV, a 13‐kW diesel generator, and a Combined dispatch strategy. The system's net present cost per unit cost of energy is $40 275 and 0.113 $/kWh for the chosen region, respectively. Compared to the other two battery technologies for hybrid systems, the zinc‐bromine flow battery technology is also shown to be the most environmentally friendly. Among the three battery technologies available, zinc‐bromine flow is best used in a particular location's hybridized operation.

Open-Source Software for Building-Integrated Photovoltaic Tiling for Novelty Architecture

Novelty architecture buildings can be tiled with conventional rectangular solar photovoltaic (PV) modules with both close-packed cells or partially transparent modules, vastly increasing renewable energy, reducing carbon emissions, and allowing for positive energy buildings. To enable this potential, in this study, for the first time, two open-source programs were developed and integrated to provide a foundation for designing and coating real-life novelty architecture buildings and objects with solar PV modules. First, a tiling algorithm was proposed and integrated into Blender that can generate solar PV modules on the face of any 3D model, and an augmented Python version of SAM was developed to simulate the performance of the resultant irregularly shaped PV systems. The integrated open-source software was used to analyze the energy performance of seven different novelty BIPVs located across the globe. The buildings’ energy performance was compared to conventional ground-based PV systems, and the results showed that the conventional arrays generate more energy per unit power than the BIPVs. The analysis reveals that the more complex the building model geometry, the less energy the building generates; however, the novelty BIPV power and energy densities far surpass conventional ground-based PV. The real estate savings observed were substantial, reaching 170% in one case where the BIPV reached 750 m in height. The BIPVs’ energy production is optimized by orienting the building via rotation and only needs to be carried out a single time for replication anywhere globally. The results show that the energy yield of the BIPV increases as the building becomes more detailed while the total power and energy decrease, indicating the need for the careful balancing of priorities in building design. Finally, the energy simulations demonstrate the potential for net-positive energy buildings and contribute to net-zero-emission cities. The findings indicate that BIPVs are not only appropriate for conventional residential houses and commercial buildings, but also for historical building replicas or monuments in the future. Further studies are needed to investigate the structural, electrical, and socio-economic aspects of novelty-architecture BIPVs.

Sustainable Manufacturing Engineering: Enhancing Product Quality through Green Process Innovations

The imperative for sustainable practices within manufacturing has become increasingly critical, driven by environmental concerns, regulatory pressures, and the evolving expectations of eco-conscious consumers. This paper investigates the role of sustainable manufacturing engineering in enhancing product quality through the implementation of green process innovations. Specifically, the study explores how sustainable manufacturing methods, including energy-efficient systems, additive manufacturing, zero-waste production, and renewable energy integration, can drive quality improvements while reducing the environmental impact of production processes. The research is grounded in a comprehensive analysis of current green innovations in the manufacturing sector, drawing on case studies of companies that have successfully balanced quality and sustainability. The findings indicate that companies adopting sustainable practices not only reduce waste and lower emissions but also experience notable gains in product durability, customer satisfaction, and brand reputation. For instance, additive manufacturing is shown to improve precision and material efficiency, while zero-waste initiatives lead to a more efficient resource cycle, which in turn supports consistent quality standards. This paper further delves into the challenges of implementing green manufacturing processes without compromising product quality, examining factors such as initial costs, technological readiness, and market adaptation. Visual data in the form of tables and graphs are presented to compare different green process innovations and their respective impacts on quality and sustainability metrics. In addition, case study summaries provide real-world examples of how leading companies have enhanced product quality through sustainable engineering approaches. This study underscores the value of sustainable manufacturing engineering as a dual-benefit strategy that can drive environmental stewardship alongside quality enhancement. The paper recommends that future research focus on the development of new, cost-effective green technologies and the application of advanced data analytics for improved process control in sustainable manufacturing. Through these efforts, the manufacturing sector can continue advancing toward a more sustainable, high-quality production paradigm.

The Analysis of Geospatial Factors Necessary for the Planning, Design, and Construction of Agricultural Biogas Plants in the Context of Sustainable Development

This spatial analysis focuses on the relevant elements regarding the use of renewable energy sources, in particular, biogas, taking into account sustainability. The characteristics of the processes of biogas formation are presented, including the technological and biological aspects of its production. The issues of agricultural biogas plant profitability are discussed using examples from Poland, analyzing the economic and financial aspects of investing in this type of plant. Geospatial analysis supported by geographic information systems (GISs) looked at factors affecting the relief of the land and also the analysis of local plans or zoning decisions for the selected site. In addition, distance relationships and geological aspects taking into account terrain, landslides, and forestation, as well as hydrological aspects relating to flood and flooding hazards, were examined. It analyzed the availability of utility networks and proximity to road infrastructure. It was also examined that the proposed project will not have a negative impact on environmental protection. The analyzed site meets favorable conditions for the construction of the proposed project, and the conclusion drawn from this study is to emphasize the importance of integrating renewable energy sources with information systems to achieve sustainable development.

Examining the Potential of Biogas: A Pathway from Post-Fermented Waste into Energy in a Wastewater Treatment Plant

Biogas has improved due to technological advancements, environmental awareness, policy support, and research innovation, making it a more cost-effective and environmentally friendly renewable energy source. The Generalized Linear Model (GLM) was employed to examine the relationship between purchased and generated energy from 2007 to 2023. Metrics such as deviance, log likelihood, and dispersion phi were examined to assess model fit. The Mann–Kendall test was utilized to detect trends in energy datasets. Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) reduction was significant, exceeding 97% from 2014 to 2023. However, treated sewage displayed limited susceptibility to biological degradation, with COD to BOD5 ratios increasing from 2.28 to 6.59 for raw sewage and from 2.33 to 7.05 for treated sewage by 2023. Additionally, the efficiency of sewage purification processes was calculated, and multivariate regression analysis was conducted on gas composition data. Principal Coordinate Ordination (PCO) and k-means clustering were used for dimensionality reduction and biogas component clustering, respectively. This research showed that biogas from the waste water treatment process can be used, particularly in methane production. Technological advancements have made biogas production more efficient, enhancing energy generation within a circular economy framework.

Maximizing Bifunctionality for Overall Water Splitting by Integrating H2 Spillover and Oxygen Vacancies in CoPBO/Co3O4 Composite Catalyst

In the pursuit of utilizing renewable energy sources for green hydrogen (H2) production, alkaline water electrolysis has emerged as a key technology. To improve the reaction rates of overall water electrolysis and simplify electrode manufacturing, development of bifunctional electrocatalysts is of great relevance. Herein, CoPBO/Co3O4 is reported as a binary composite catalyst comprising amorphous (CoPBO) and crystalline (Co3O4) phases as a high‐performing bifunctional electrocatalyst for alkaline water electrolysis. Owing to the peculiar properties of CoPBO and Co3O4, such as complementing Gibbs free energy values for H‐adsorption (ΔGH) and relatively smaller difference in their work functions (ΔΦ), the composite exhibits H2 spillover (HS) mechanism to facilitate the hydrogen evolution reaction (HER). The outcome is manifested in the form of a low HER overpotential of 65 mV (at 10 mA cm−2). Moreover, an abundant amount of surface oxygen vacancies (Ov) are observed in the same CoPBO/Co3O4 composite that facilitates oxygen evolution reaction (OER) as well, leading to a mere 270 mV OER overpotential (at 10 mA cm−2). The present work showcases the possibilities to strategically design non‐noble composite catalysts that combine the advantages of HS phenomenon as well as Ov to achieve new record performances in alkaline water electrolysis.

Production Simulation of Stimulated Reservoir Volume in Gas Hydrate Formation with Three-Dimensional Embedded Discrete Fracture Model

Natural gas hydrates (NGHs) in the Shenhu area of the South China Sea are deposited in low-permeability clayey silt sediments. As a renewable energy source with such a low carbon emission, the exploitation and recovery rate of NGH make it difficult to meet industrial requirements using existing development strategies. Research into an economically rewarding method of gas hydrate development is important for sustainable energy development. Hydraulic fracturing is an effective stimulation technique to improve the fluid conductivity. In this paper, an efficient three-dimensional embedded discrete fracture model is developed to investigate the production simulation of hydraulically fractured gas hydrate reservoirs considering the stimulated reservoir volume (SRV). The proposed model is applied to a hydraulically fractured production evaluation of vertical wells, horizontal wells, and complex structural wells. To verify the feasibility of the method, three test cases are established for different well types as well as different fractures. The effects of fracture position, fracture conductivity, fracture half-length, and stimulated reservoir volume size on gas production are presented. The results show that the production enhancement in multi-stage fractured horizontal wells is obvious compared to that of vertical wells, while spiral multilateral wells are less sensitive to fractures due to the distribution of wellbore branches and perforation points. Appropriate stimulated reservoir volume size can obtain high gas production and production efficiency.

Polymeric Materials in Energy Conversion and Storage

Energy conversion and storage devices based on polymeric materials are emerging as a promising avenue for renewable power sources [...]