Renewal Type Research Articles

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.

Optimal Management of Energy Storage Systems in Hospitals with Quantum Spherical Fuzzy Decision-Making Modelling

The purpose of this study is to identify prioritized strategies to increase the effectiveness of energy storage investments in hospitals. For this purpose, 5 literature-based criteria affecting energy storage investments in hospitals are identified. These criteria are weighted by the quantum spherical fuzzy DEMATEL method. On the other side, 4 different renewable energy alternatives are identified. The performance of these alternatives are ranked with quantum spherical fuzzy TOPSIS approach. It is determined that storage capacity is the most critical factor to increase the effectiveness of the energy storage systems in the hospital. Similarly, technological infrastructure is another key issue for the development of this process. However, it is also seen that security issues, legal effectiveness and financial situations have the lower weights. In addition to them, the ranking results demonstrate that wind energy is the most appropriate renewable energy type with respect to the energy storage performance of the hospitals. Geothermal energy can also be considered for this situation. On the other hand, solar and hydropower energy types have lower performance in this framework.

Analysis of 27 supervised machine learning models for the co-gasification assessment of peanut shell and spent tea residue in an open-core downdraft gasifier

The producer gas (PG) obtained through thermochemical processing of the various renewable biomass types contributes to Sustainable Development Goal-7 (SDG-7). Hence, this study examined 27 supervised and multiple-input single-output ML models in terms of performance metrics and accuracy to predict CO, H2, CH4, and CO2 compositions, as well as PG's HHV in the co-gasification of peanut shell (PS) and spent tea residue (STR). Multiple trial experiments were tested with various equivalence ratios (ERs) and mixing ratios (MRs) on a 90 m3/h gas-yield open-core, down-draft gasifier with air as the gasification medium. About 18 models were chosen after evaluating their performance metrics in estimating relevant parameters. The accuracy of those models is assessed based on 12 sample runs with varying ER and MR. The findings revealed that 16 models from the linear, neural network, support vector machine, Gaussian process, tree, and ensemble categories were reliable ML models. The chosen 16 models' R2 values for CO, H2, CH4, CO2, and HHVPG are above 0.931, 0.937, 0.962, 0.806, and 0.971, respectively, with the exception of TRE. Additionally, the models demonstrated a prediction accuracy of >95 % for all of the investigated parameters in the co-gasification of PS and STR when compared to random experimental runs.

Exploring the impacts of entrepreneurship indices on renewable energy mix: A cross-country study

This research analyzes the impact of eleven entrepreneurship indicators on renewable energy development across 14 countries from 2002 to 2019. Utilizing Kao's test for variable cointegration and the Panel Fully Modified Ordinary Least Squares (PFMOLS) model, our research highlights financial development's critical role in shifting from traditional to newer renewable energies like wind, solar, and bioenergy. Results indicate that specific entrepreneurship indicators, such as commercial infrastructure, market openness, and entrepreneurship education at the primary level, influence renewable energy types differently. For instance, these factors are favorable for hydropower but negative for wind and solar. Conversely, other indicators exhibited the opposite effects. For instance, Research and Development (R&D) transfer, governmental programs, and internal market dynamics positively impacted wind and solar energy sources but negatively affected hydropower and bioenergy. These findings underscore the multifaceted nature of entrepreneurial activities as a driving force behind the development of renewable energies, which highlights the need to reconsider regulations, support mechanisms, and educational frameworks related to entrepreneurship in alignment with climate change, making our research directly relevant to policymakers and practitioners in the environmental and energy sectors. To align with climate change goals better, the research in this study recommends enhancing financial mechanisms for diverse renewable technologies, revising educational frameworks to embed entrepreneurship focusing on renewable innovation, and adjusting governmental programs to support targeted renewable energies.

Effects of thermoelasticity induced aperture variation on performances of Enhanced geothermal system

Geothermal energy, as one of the renewable energy types, has great potential to balance the variable energy supply from photovoltaic and wind energy types. This, however, requires the development of an Enhanced Geothermal System (EGS). Injecting cold water into deep geo-reservoirs induces thermoelastic deformation and changes the fracture apertures, which may significantly affect the EGS lifetime and energy performance. In this case, this study develops a fully coupled thermal–hydraulic-mechanical model to investigate the impacts of temperature, pressure, and aperture heterogeneity on the alterations of fracture aperture. Then, considering the reservoir lifespan, the research takes a further step into the influence of heterogeneous aperture variation on EGS production temperature and long-term energy performance. Results show that aperture significantly varies once a temperature breakthrough occurs in the production well for both homogeneous and heterogeneous aperture fields. The thermoelasticity-induced aperture variations enhance water flow rate, leading to a considerable increase in reservoir heat production rate, but a shorter EGS lifespan. Furthermore, temperature variation shows a more substantial influence on aperture alteration compared to pressure change. Additionally, a sensitivity analysis indicates that the 30-year total energy output is proportional to the injection/production pressures and injection temperatures. However, the fracture with either excessively large or small initial apertures leads to worse EGS energy performance.

Assessing the carbon mitigation impact of energy choices in China: a focus on renewable energy and thermal efficiency improvement

ABSTRACT This study estimates the carbon mitigation effects of various energy choices, focusing on renewable energy (RE) adoption and thermal efficiency improvement. We compiled a comprehensive panel data covering 2,641 counties from 2003 to 2017 and employed a dynamic panel model for the analysis. Our results suggest that the adoption of wind power and thermal efficiency improvement, with the latter indicated by the adoption of large thermal power plants, significantly reduces carbon emissions. Notably, increasing wind power capacity exhibits a more substantial marginal reduction effect than increasing large thermal capacity. Moreover, the mitigation impact of RE is more substantial in regions with diverse renewable power types and higher renewable capacity. These results provide robust evidence regarding thermal efficiency improvement’s role in carbon mitigation and underscore the growing environmental benefits of RE as its share in installed capacity increases. Our findings emphasize the necessity of policies that incentivize the utilization of various RE types and target regional environmental efficiency gaps, which are crucial for achieving enhanced carbon mitigation during the energy transition.

To replicate or to renew your business model? The performance effect in dynamic environments

It is often assumed that business model innovation drives firm performance, especially when firms operate in highly dynamic environments. However, despite the rise in research on business models, there is little systematic evidence of how various levels of environmental dynamism actually influence the performance effects of two basic types of business model innovation, namely replication (i.e., scaling up and improving an existing business model) and renewal (i.e., introducing a new business model). In this paper, we delineate a conceptual distinction between these two types of business model innovation and investigate how environmental dynamism impacts their performance outcomes. Based on a cross-industry survey that includes both SMEs and larger firms, we show that environmental dynamism weakens the positive effects of business model replication on firm performance. By contrast, in environments where the level of dynamism is intermediate, rather than high or low, environmental dynamism strengthens the performance effects of business model renewal. We discuss how these insights contribute to the business model innovation literature and how they can provide top managers with guidance on when and how to innovate a business model to turn it into a competitive advantage.

Thermodynamic, exergetic and environmental evaluation and optimization of a bio-fuel fired gas turbine incorporated with wind energy derived hydrogen injection

The fluctuating nature of wind energy and shortage of biomass resources, as two types of renewables, can be fulfilled via their hybridization. In this respect, present research proposes a hybrid biomass/wind energy driven power generation framework based on combined gas turbine-Rankine cycle scheme. The gas turbine includes a reheat stage where the produced hydrogen is added to the combustion chamber for increasing flue gas temperature to enhance output power. The injected hydrogen is generated via a water electrolyzer which is powered by electricity from the wind turbines. The proposed scheme of biomass/wind powered system leads to a reduction in biomass consumption and will fulfill the fluctuations and non-continuous availability of wind energy. To appraise the feasibility of developed hybrid scheme, thermodynamic first and second law-based analyses were performed. Also, the exergo-environmental evaluation of the hybrid plant is conduced using three exergo-environmental indices. Finally, optimum operation conditions of the proposed hybrid plant is determined based on the minimization of environmental damage index. The results under optimum operation indicate that, the proposed hybrid power generation plant yields exergy efficiency of 47.35 % with environmental damage index of 0.0104.

How does urban renewal affect residential segregation in Shenzhen, China? A multi-scale study

Increasing residential segregation is emerging as a hindrance to urban sustainability. Urban renewal projects that claim alignment with sustainable development goals still lack comprehensive studies of their impact on social segregation, as evidenced by the ongoing scholarly debate over whether urban renewal has a positive or negative effect on social segregation. This paper explores the dynamics of urban spatial segregation, analyzes the role of urban renewal on segregation, and bridges the gap in existing research by considering dynamic changes, multiple spatial scales, and diverse renewal types. Using multi-source data – house price data, planning permit data and points of interest –stepwise regression models are combined with t-test methods to examine the impact of multiple types of urban renewal on local and regional residential segregation in Shenzhen. Our findings are as follows: 1) Income-based segregation in Shenzhen increased from 0.77 to 0.81 across neighborhoods, from 0.62 to 0.73 across sub-districts, and from 0.58 to 0.67 across districts between 2000 and 2020, therefore increasing at all scales but with more pronounced growth of segregation observed between units at larger scales; 2) Urban renewal can lead to greater income similarity amongst residents of a sub-district, by attracting more high-income people to move in, but this can lead to increased residential segregation of high- and low-income people at the macro-scale. 3) When assessing the impact of urban renewal on segregation, it is recommended to consider the variations in outcomes resulting from temporal changes, spatial scales, the types of renewal, the types of segregation, and the stages of urbanization. Understanding this process can help promote socially sustainable urban renewal projects.

When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality.

Allocation of non-uniform complex of resources in production systems. Scheduling and correction of deadlines

The problem of planning a job complex with the use of resources of various types − renewable (performers who can differ with the productivity) and several types of non-renewable is considered. We allow interruptions, and switching from one performer to another and performing one work simultaneously by several performers. The available number of performers at different times is not constant, and their productivity may vary. A developed polynomial algorithm finds the optimal allocation of resources and builds the optimal schedule of jobs. A pseudopolynomial algorithm for finding the optimal allocation of resources of minimal cost has been developed. These algorithms based on building a flow network model and modifying the packing procedure. An algorithm for the optimal allocation of resources and the construction of an optimal schedule for the case of a heterogeneous set of works is proposed.

IMPROVED LEVEL OF TECHNOGENIC SAFETY IN PLANTS INTENDED MUNICIPAL SOLID WASTE INCINERATION

Solid municipal waste can be an alternative and renewable type of fuel. Waste incineration provides effective disposal, significant volume reduction and utilization of the energy potential of the carbon waste part. In order to protect the components of the biosphere and service personnel from harmful substances that are formed in the furnace space, it is first necessary to assess the chemical composition and volume of emissions. The purpose of the work is to study the process of burning municipal waste, determine the heat energy obtained, determine the amount of air required for the complete combustion reaction, and determine the volume of flue gases produced as a result of combustion. To achieve the goal of the research, a complex of methods of system analysis and the method of data analysis was applied. An analysis of modern international literary sources, an analysis of the morphological composition of the combustible part of solid household waste, and an analysis of the interaction of chemical substances was carried out. For the research, several components of waste were collected, which were conditionally divided into two main groups - paper and plastic. The first group includes waste, which includes wood, cardboard, and paper. The second group (plastic) includes waste, which includes plastic in the form of scraps of polyethylene film, disposable dishes. As a result of the research, a theoretical volume of combustion products was obtained for the further design of the system of protection of the environment and service personnel from emissions of thermal disposal of solid household waste. Research results can be used in the design of municipal waste incineration equipment. The system of using the heat of flue gases generated after burning waste to dry the waste before feeding it to the furnace is of great importance for saving additional fuel.

An Application of Photovoltaic Appropriate Technology as Garden Lighting at Tourist Area of Gangga Murmas Tree House North Lombok District

Park lighting in the Gangga Murmas Tree House Tourism Area, which is more precisely Gangga Hamlet, Genggelang Village, Gangga District, North Lombok Regency, is not sufficient. Without park lighting, tourist locations will resemble a dead zone at night and experience a decline in visitors. Therefore, the Community Service Team of the Madura State Islamic Institute through the 3T area community empowerment service provides a solution to illuminating the Gangga Murmas Tree House Tourism Area by utilizing new renewable energy Photovoltaic monocrystalline type to provide lighting at night. The installation of landscape lighting using polycrystalline technology is determined by the outcomes of location surveys and observations. The implementation carried out in the Gangga Murmas Tree House Tourism Area was carried out in several stages, namely: observation, preparation of garden light design, training and maintenance, performance testing, and tool evaluation. After the project was finished in two months, a solar power plant with a 2800Wh capacity that can power 40 lamps with a combined 120Watt capacity was created. The placement of garden lights to improve the tourism sector also received a positive response from the community and the manager of the Gangga Murmas Tree House Tourism Area.
 Keywords: Photovoltaic Appropriate Technology, Garden Lighting

Typological differentiation and time-series effects of urban renewal on housing prices

Urban renewal is a critical avenue and strategic tool for achieving high-quality and sustainable development, and the residential market plays a vital role in promoting urban renewal and urban growth. However, the impact of urban renewal on housing prices remains inconclusive, closely tied to the characteristics of the study area, the sources of research data, and so on. To address this, we employ the difference-in-difference method and a mixed panel dataset of housing transactions from 2010 to 2021 to analyze in detail the effects of different urban renewal types (Industrial Renewal, Residential Renewal, and Commercial Renewal) on surrounding housing prices in Bao'an District at different renewal phases (announcement, start, and completion). We found that Industrial Renewal exerts the most significant impact on housing prices at the beginning and completion of renewal, followed by Residential Renewal and Commercial Renewal. Moreover, Urban renewal generates both positive and negative externalities on housing prices, especially in the case of numerous small-scale renewal projects. The findings suggest that urban renewal should be supported by systematic research on renewal types, the establishment of scale entry threshold, and the monitoring of the entire process.

Investigating a Renewable-Resource-Targeting Mobile Aquaculture System Using Route Optimization Based on Optimal Foraging Theory

Aquaculture systems require careful consideration of location, which determines water conditions, pollution impacts, and hazardous conditions. Mobility may be able to address these factors while also supporting the targeting of renewable energy sources such as wind, wave, and solar power throughout the year. In this paper, a purpose-built mobile aquaculture ship is identified and modeled with a combination of renewable energy harvesting capabilities as a case study with the objective of assessing the potential benefits of targeting high renewable energy potentials to power aquaculture operations. A route optimization algorithm is created and tuned to simulate the mobility of the aquaculture platform and cost-basis comparisons are made to a stationary system. The small spatial variability in renewable energy potential when combining multiple resources significantly limits the benefits of a mobile, renewable-targeting aquaculture system. On the other hand, the consistent energy harvest from a blend of renewable energy types (13 kW installed wind capacity, 661 m2 installed solar, and 1 m characteristic width wave-energy converter) suggests that the potential benefits of a mobile platform for offshore aquaculture (mitigation of environmental and social concerns, any potential positive impact on yields, hazard avoidance, etc.) can likely be pursued without significant increases in energy harvester costs.

From guidelines to current practices: Suboptimal hypertension management in France

In France, the prevalence of hypertension is higher than 30%. Although treatment guidelines have been well established over the last twenty years, the national blood pressure control rate is below the average of high-income countries. This observational study aimed to describe the antihypertensive prescription behaviours of primary care physicians (PCPs) in France and to assess their compliance with current French guidelines, focusing on three specific prescription issues and their potential repercussions on blood pressure control: treatment initiation, treatment renewal or change and type of triple therapy. Prescription data were retrieved using the IQVIA longitudinal patient database (LPD), which delivers real-world data insights from French primary care electronic medical records (EMR). The average number of prescribed therapeutic agents was 1.9 per patient, with 39.3% monotherapy prescriptions. Treatment initiation represented 7.2% of all antihypertensive prescriptions. At treatment initiation, 22.5% of patients were prescribed dual therapy. The proportion of treatment renewal in the same therapeutic class was 74.3% while the proportion of treatment change was 18.5%. Of these, only 6.3% of patients received an additional therapy. Lastly, 35.7% of triple therapies were consistent with the recommended combinations. In conclusion, this study provides evidence of therapeutic gaps in hypertension management in France. The low blood control rate may be attributed to PCPs' therapeutic inertia and lack of knowledge of treatment guidelines. All stakeholders should commit to rapid corrective action in order to provide patients with the best care.

Impact of urban renewal on urban heat island: Study of renewal processes and thermal effects

This study examines the impact of different types and processes of urban renewal on the urban heat island (UHI) effect. The research categorizes renewal projects based on changes in buildings, underlying surfaces, and functions. Using the Spearman correlation coefficient and LOWESS method, the study analyzes the relationships between cooling effects and impact factors. The results reveal that transforming industrial areas into commercial or residential zones and transitioning from compact mid-rise to open high-rise structures have significant cooling effects. However, the renewal implementation of the latter transformation can exacerbate the local UHI, suggesting the need for optimizing the timeline of such projects. Increasing vegetation cover plays a crucial role in mitigating the UHI, while higher floor area ratios and building volumes do not necessarily intensify the UHI. To improve the urban ecosystem, urban renewal planning should prioritize the creation of blue and green spaces, incorporation of natural infrastructure, and reduction of impervious surfaces. These findings have implications for urban renewal policies, selection of preferred renewal types, and insights into the renewal process.

Integration of the Machine Learning Algorithms and I-MR Statistical Process Control for Solar Energy

The importance of solar power generation facilities, as one of the renewable energy types, is increasing daily. This study proposes a two-way validation approach to verify the validity of the forecast data by integrating solar energy production quantity with machine learning (ML) and I-MR statistical process control (SPC) charts. The estimation data for the amount of solar energy production were obtained by using random forest (RF), linear regression (LR), gradient boosting (GB), and adaptive boost or AdaBoost (AB) algorithms from ML models. Data belonging to eight independent variables consisting of environmental and geographical factors were used. This study consists of approximately two years of data on the amount of solar energy production for 636 days. The study consisted of three stages: First, descriptive statistics and analysis of variance tests of the dependent and independent variables were performed. In the second stage of the method, estimation data for the amount of solar energy production, representing the dependent variable, were obtained from AB, RF, GB, and LR algorithms and ML models. The AB algorithm performed best among the ML models, with the lowest RMSE, MSE, and MAE values and the highest R2 value for the forecast data. For the estimation phase of the AB algorithm, the RMSE, MSE, MAE, and R2 values were calculated as 0.328, 0.107, 0.134, and 0.909, respectively. The RF algorithm performed worst with performance scores for the prediction data. The RMSE, MSE, MAE, and R2 values of the RF algorithm were calculated as 0.685, 0.469, 0.503, and 0.623, respectively. In the last stage, the estimation data were tested with I-MR control charts, one of the statistical control tools. At the end of all phases, this study aimed to validate the results obtained by integrating the two techniques. Therefore, this study offers a critical perspective to demonstrate a two-way verification approach to whether a system’s forecast data are under control for the future.

Incentive Mechanisms to Integrate More Renewable Energy in Electricity Markets in China

China has made significant progress in developing renewable energy, but challenges in integrating variable sources like wind, solar, and hydro power persist. Existing research has a regional focus and lacks a comprehensive understanding of integration challenges in specific regions. Moreover, research concentrates on individual energy types rather than multiple sources. Addressing these challenges requires a deeper analysis of market rules, incentives, and mechanisms for integrating numerous renewable energy types. The existing research also overlooks crucial aspects like energy consumption, grid planning, and power market mechanisms. To promote renewable energy integration effectively, policymakers must address these interconnected factors through comprehensive investigations and research efforts. This study proposes tailored solutions to encourage integration in China based on international experiences, such as Brazil’s contract markets and electricity redistribution mechanism, the Nordic spot market, and California’s negative pricing mechanism. The strategies derived from global practices for China’s renewable energy integration include diverse trading mechanisms, expanded contract markets, optimized local consumption, fortified grid infrastructure, and improved market mechanisms.

Ocean Energy: Markets – Currency – Impact. Dimension of & Choices in the Technology Development Space

Reflecting in the acceleration of the changes in ecological, climatological and generally planetary health, it is critical to employ those energy source as well and those energy used that are of the highest ratio of benefit to effort and deliver the most valuable and impactful, tangible contribution in service of natural commons and common societal good. Such considerations hold for all ocean energy types and especially for ocean wave energy.
 Thus, it is not only important to consider the resource that is converted into the standard form of usable energy, that is, in the form of electricity and to deliver to the most prominent marketplace, that is, the continental grid; it is equally important to consider the use, purpose and impact after converted energy.
 Reflecting on the entire value chain from marine renewable energy to a) usable energy to b) the actual use and purpose of the energy may lead to highly impactful implementations with more direct delivery of the renewable energy to the valued application. In such more direct paths from resource to impact the extracted energy and the applied energy is a mean to the purpose rather than a means to an end.
 Assessments of marine renewable energy markets other than powering the continental grid, such as Powering the Blue Economy, have been investigated and numerous research efforts are underway. However, to fully maximize the achievable impact of ocean wave energy it is critical to extend the consideration from replacing the energy source in existing applications to the enablement of highly impactful applications that are currently not existing or are not operated at the magnitude when powered by ocean waves.
 Highest effectiveness is achieved when the uniqueness of the renewable energy form matches the unique needs of the targeted application. For ocean wave energy the uniqueness lies in relative consistency, high degree of forecastability, energy density and the ubiquitous nature across the oceans. These provide a plethora of opportunities to serve markets and purposes that are directly in or based on the oceans.
 Technology development progress indicators such as Technology Readiness Levels (TRL) and Technology Performance Levels (TPL) are typically used to span up the technology development space and provide a framework and orientation for the desired technology development trajectories. Based on the description of the motivations above the paper and presentation with introduce and describe additional and alternative technology development indicators that directly point and guide the development towards impactful application and purpose as the desired technology development goal. 
 In order to provide a clear understanding of impact markets and the associated values, thus, their specific currency these are best served in, three impact markets are presented in detail as concrete examples. These support planetary and ocean health in different ways through carbon capture, acceleration of the deployment of all forms of marine renewable energy types and enabling the implementation and enforcement of environmental legislation. Beyond these, a dozen of others impact markets are listed to provide an overview of impact oriented markets and applications.