Effects Of Renewable Energy Sources Research Articles

Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs

This study offers an in-depth thermodynamic analysis and optimization of an integrated renewable energy system that merges a double-flash geothermal system with a transcritical carbon dioxide Rankine cycle, utilizing machine learning algorithms. The innovative design aims to maximize the concurrent generation of heat and electricity, ultimately benefiting environmental sustainability and energy security. By employing regression machine learning algorithms, the research evaluates and enhances system performance, achieving remarkable R-squared accuracy levels of 98.86 % for heating output and 99.89 % for power output predictions. The thermodynamic modeling, which has been validated against recognized benchmarks, confirms the accuracy of the system's design. Optimization findings indicate that operating pressures between 840 and 870 kPa and pressure ratios of 1.56–1.60 deliver optimal outputs, with power production between 2582 and 2585 kW and heating output ranging from 12260 to 12280 kW. The system reaches its maximum performance at a pressure of 850 kPa and a pressure ratio of 1.57, resulting in a power output of 2583.97 kW and a heating output of 12279.3 kW. These results highlight the potential of combining advanced thermodynamic systems with machine learning methodologies to improve the efficiency and effectiveness of renewable energy sources.

Can renewable energy sources alleviate the pressure of military expenditures on the environment? Empirical evidence from Turkiye

This study analyzes the potential of renewable energy sources to reduce the environmental impact of military expenditures in Turkiye. ARDL method is preferred in the analysis using annual data for the period 1990-2021. In addition, an interaction term is added to the model to determine the effectiveness of renewable energy sources. The results show that military expenditures have a positive effect on CO2 emissions in the short and long run with coefficients of 0.260 and 0.196, respectively. Moreover, renewable energy use has a statistically significant negative effect on CO2 emissions in the short and long run with coefficients of -0.119 and -0.120, respectively. GDP has a positive effect on CO2 emissions in the short and long run with coefficients of 0.162 and 0.193, respectively. Although population growth does not have a statistically significant effect in the short run, it is found to increase CO2 emissions in the long run with a coefficient of 0.095. Moreover, the interaction term shows that renewable energy use reduces the environmental impact of military expenditures in Turkiye in the short and long run with coefficients of -0.130 and -0.140, respectively. The results indicate that renewable energy use can play an important role in mitigating the environmental impacts of military expenditures.

Understanding the Influence of Wind and Solar PV on Socioeconomic and Environmental Trends: A Non-causality Perspective

This paper investigates the non-causality perspective of economic growth, investment, social well-being, employment, GHG emissions on renewable energy sources (RES) (wind and solar PV), providing a comprehensive overview of renewable technologies that effect on socio-economic and environmental drivers. The analysis and enhancing linear regression techniques, addressing cross-country RES installed capacity heterogeneity, and applying time-lags techniques to better understand the temporal effect of RES´s investment. The study tested: I. economic growth in a country is related to the development of RESs, employment, investment. II. Increased RESs share positively impacts social well-being. III. RESs implementation reduces GHG emissions. Our findings suggest that RES positively influenced economic growth over time for countries with higher installed capacity. However, this statistically significant is not observed across countries with lower installed capacity nor across all indicators, like social well-being, employment, investment, which show modest growth trend over time. GHG emissions also showed an inverse trend, suggesting the needs the renewable electricity´s expansion accompanied by additional mitigation measures to reduce emissions. One limitation is the temporal restriction, which limits the assessment of long-run trends. Future research should focus on gathering a larger dataset for long-run trends analysis.

Optimal techno-economic assessment of isolated microgrid integrated with fast charging stations using radial basis deep learning

The global transportation electrification commerce sector is now booming. Stakeholders are paying an increased attention to the integration of electric vehicles and electric buses into the transportation networks. As a result, there is an urgent need to invest in public charging infrastructure, particularly for fast charging facilities. Consequently, and to complete the portfolio of the green environment, these fast-charging stations (FCSs) are designed using 100% of renewable energy sources (RESs). Thus, this paper proposes an optimization model for the techno-economic assessment of FCSs comprising photovoltaic and wind turbines with various energy storage devices (ESDs). In this regard, the FCS performance is evaluated using flywheels and super capacitors due to their high-power density and charging/discharging cycles and rates. Then, optimal sizing of these distributed generators is attained considering diverse technical and economical key performance indicators. Afterwards, the problem gets more sophisticated by investigating the effect of RES’s uncertainties on the selection criterion of the FCS’s components, design and capacity. Eventually, as an effort dedicated to an online energy management approach, a deep learning methodology based on radial basis network (RBN) is implemented, validated, and carried out. In stark contrast to conventional optimization approaches, RBN demonstrates its superiority by obtaining the optimum solutions in a relatively short amount of time.

Automatic Generation Control in Renewables-Integrated Multi-Area Power Systems: A Comparative Control Analysis

Electrical load dynamics result in system instability if not met with adequate power generation. Therefore, monitoring and control plans are necessary to avoid potential consequences. Tie-line-bias control has facilitated power exchange between interconnected areas to cope with load dynamics. However, this approach presents a challenge, as load variation in either area leads to frequency deviations and power irregularities in each of the interconnected areas, which is undesirable. The load frequency control loop method is used to address this issue, which utilizes area control errors. This study focuses on the control of inter-area oscillations in a six-area power system under the effect of renewable energy sources. It evaluates the area control errors in response to changes in load and the penetration of renewable energy into the system. To mitigate these errors efficiently, an adaptive-PID controller is proposed, and its results are compared with PI and PID controllers optimized with heuristic and meta-heuristic algorithms. The findings demonstrate the superiority of the proposed controller over traditional controllers in mitigating tie-line power errors and frequency deviations in each area of the interconnected power system, thus helping to mitigate inter-area oscillations and restore system stability.

Analyzing the Relationship between Renewable Energy Sources, Economic Growth and Energy Consumption in Greece

Renewable energy sources are one of the important economic factors of today. Energy resources have a great place for economic growth. There are many types of renewable energy sources, each of which is one of the indispensable elements for the development and development of countries. In this study, which measures the importance of energy consumption within the scope of economic growth and renewable energy, the effects of renewable energy sources and economic growth on energy consumption are investigated. In the study, the relationship between renewable energy sources, economic growth and energy consumption was examined by making panel cointegration analysis for Greece between 1997-2015. According to the results of the analysis, the panel data model established is significant at the 95% level. The independent factors explain 78% of the dependent variable's variation, according to R2. Energy consumption and renewable energy consumption were negatively correlated. A significant and positive relationship was found between economic growth and energy consumption at the 95% confidence level. An 1% increase in economic growth will increase energy consumption by about 15%. This result obtained because of the estimation also supports the theoretical expectation.

The Impact of Renewable Energy on Sustainable Economic Growth in Afghanistan

The present study has been conducted to investigate the impact of renewable energy on the sustainable economic growth of Afghanistan. This research focuses on examining the ranking of the effects of renewable energy sources on economic growth. In this study, secondary data sources were utilized to describe the situation in Afghanistan regarding renewable energy and its utilization possibilities. Meanwhile, primary data from 195 experts in energy, water, and electricity, environmental specialists, economists, and several firms in Kabul were collected to assess its economic impacts. The sample was selected through simple random sampling. A questionnaire was used as the data collection tool, designed structurally based on the Likert spectrum and theoretically supported by various economic theories. The reliability of the questionnaire was ensured using Cronbach's alpha, which yielded satisfactory results (α = 0.94). The collected data were analyzed using SPSS software through various statistical methods such as KMO, Bartlett's test, factor analysis, composite reliability, convergent validity, discriminant validity, analysis of variance, Pearson correlation, regression analysis, and the coefficient of variation. The findings indicate that hydro energy can significant contribute to a positive change of 0.358% and solar energy can significant contribute to 0.412% in sustainable economic growth in Afghanistan. But wind energy has insignificant impact on economic growth in Afghanistan. The results of the study suggest that solar, hydro, and wind energy can have considerable effects on sustainable economic growth in Afghanistan. In conclusion, the research results confirm the hypothesis, asserting that the uses of renewable energy contribute to improving the sustainable economic growth in Afghanistan.

The Opinions of Eighth Grade Students on Renewable Energy Sources in their Environment: A Local Perspective

Renewable and local energy sources have great importance in meeting the energy needs of individuals. Students’ opinions on renewable energy sources (RES) in the environment they live in are considered important as they will be decision-makers in the future. The current study is aimed at determining the opinions of eighth grade students about RES in their environment. In this research, phenomenology design from the qualitative research method was used. 31 eighth-grade students participated in the study in the 2021-2022 school year from Gaziantep's Nizip district. The participating students were determined by using convenience sampling, which is one of the purposive sampling methods. The research, in which a semi-structured interview form was used, was analyzed according to content analysis. The findings revealed that, according to the participants, the most used renewable energy in their environment is solar energy. The students’ answers about the characteristics of RES showed that they have knowledge about this subject. However, their giving only solar, wind, and hydroelectric energies as examples of RES shows that their opinions on this subject are limited. The students’ answers about the positive effects of RES on the environment showed that their awareness is high. However, it was revealed that the participants did not have enough awareness about this issue when the negative effects of RES were examined. Given both the local and global importance of energy-related issues, it is recommended to discuss the characteristics specific to different regions in future research.

Investigation of the relationship between renewable energy, natural gas, and coal consumption with economic growth in Turkey: evidence from augmented ARDL approach.

Energy is an indispensable requirement for the sustainable development of countries. Turkey has been trying to increase the use of renewable sources in electricity energy production with the policies it has implemented recently. This study investigates the effect of disaggregate energy consumption on economic growth in Turkey via the Augmented ARDL. Robust results are obtained by Augmented ARDL in econometric analysis. In this context, it is to examine the impact of renewable energy, natural gas, and coal consumption. Considering the 2001 crisis in Turkey, we add a dummy variable to the cointegration equation. The paper employs the recently developed augmented ARDL approach in the presence of one structural break to investigate annual time series data during the period 1988-2018. The results obtained in this study showed that all variables were statistically significant eventually. Long-term estimation results suggest that among the energy sources examined in the study, on economic growth has a positive effect coal consumption, natural gas consumption, and renewable energy. Moreover, empirical results indicated that economic growth and energy consumption also contribute to environmental damage. On the contrary, natural gas both increases economic growth and is effective in increasing environmental quality. The fact that the positive effect of renewable energy sources on economic growth eventually is greater than natural gas is the most striking finding of the study. In line with these results, it can be said that Turkey can reduce its energy dependence by increasing the use of domestic and renewable energy sources and providing sustainable economic growth.

The effects of renewable energy sources on Turkiye's economic growth: ARDL estimation.

Hydroelectric power plants have been in use for more than a century in countries with rich river resources owing to their cheaper installation costs. Hydroelectric power plants, which have particular importance for the economic growth of developing countries, have been generating electricity in Turkiye over many decades, since the early 1900s. The ultimate objective of the study is to observe the relationship between Turkiye's hydroelectric power generation and its economic growth, which is rarely addressed in the literature, by using recent data. Aimed in the empirical analysis are to test the impact of renewable energy use on economic growth in Turkiye between the years 1965 and 2019 and, in particular, to determine the role and importance of hydroelectric energy, which has an important historical background in respect of Turkish economy, in this relationship. In the analysis part of the study, firstly, unit root analyses were performed, and the ARDL estimator was made, which is the most appropriate estimator among the series with different orders of stationarity. In addition to the diagnostic tests showing whether the ARDL estimator was an appropriate estimator, findings with respect to causality between the variables were revealed with the Toda-Yamamoto causality test, which allows for different orders of stationarity of the series. According to the results of the ARDL estimator, which allows to examine the short and long-term results of the independent variables, it was concluded that renewable energy had no significant effect on economic growth in the long and short run, while hydroelectric energy has increased economic growth in the long run in the analyzed period. In Turkiye, which is highly dependent on foreign for energy production, the contribution of energy consumption to economic growth in the long run was found to be negative.

Planning the Development of Electricity Generating Capacity in a One-Zone Electric Power System with a High Share of Renewable Energy Sources

The article addresses matters concerned with planning the generating capacity in an electric power system with a high share of renewable energy sources. A stochastic nature of renewable energy sources (RES) makes them very different from conventional power plants. The RES power output depends on weather conditions, due to which some power system operators do not include them in the power balance. This leads to an excess of installed generating capacity in the electric power system and growth of electricity tariffs for consumers. Probabilistic assessments of system adequacy have shown that RES affect the power balance in the power system and do not require to be fully backed up by conventional generation. The article presents the results of calculating the system adequacy for a test IEEE scheme with different share and structure of renewable energy sources. It is shown that the effect of RES on the power balance is governed not only by the annual electricity output, but by the correlation between the RES power output and load curves. A large share of RES in a power system, entails the need to alter the requirements not only for the conventional generating capacities, but also for their structure. The article presents the results of optimizing the composition of generating equipment for different shares of RES in a power system. It has been shown that, if there are no RES in the power system, preference is given to less maneuverable, but cheaper generation units. With increasing the share of RES in the power system, so does the share of more expensive highly maneuverable units. A method of planning the generation capacity development for a single-zone power system is proposed. The value of the generation capacity margin has been determined based on the system adequacy calculation, and the mix of generating capacities is refined proceeding from optimization of the generating units loading.

A chaotic hybrid optimization technique for solution of dynamic generation scheduling problem considering effect of renewable energy sources

A chaotic hybrid optimization technique for solution of dynamic generation scheduling problem considering effect of renewable energy sources

The Effect of Renewable Energy on Energy Import Dependence: An Empirical Analysis in Turkey

Energy import dependency has remained one of the most important problems of countries that cannot meet their energy needs from domestic sources from past to present. Countries with insufficient resources in terms of fossil energy sources have met their energy demand through imports. This situation has caused countries to become dependent on external resources. For this reason, Turkey’s energy import dependency has increased continuously; according to the data published by EUROSTAT as of 2018, Turkey is foreign-dependent with approximately 74%. This situation has brought the issue of energy supply security to the agenda in Turkey. For this reason, it is important to examine Turkey’s energy import dependency and to propose solutions according to the results obtained. In this study, the effect of renewable energy sources on energy import dependency in Turkey during 1990-2018 was analyzed using the ARDL bounds test approach. The working results have determined that renewable electricity production, GDP per capita, urban population growth, and world natural gas prices have a statistically significant effect on energy import dependency. World oil prices were not statistically significant. As a result, renewable energy production reduces energy import dependency, while the most important determinant is GDP per capita.

The dynamic analysis of renewable energy's contribution to the dimensions of sustainable development and energy security.

In sustainable development, energy is critical in human activities and shapes a sustainable future. Thus, it is an unignorable element in human development. This paper analyzes the contributions of renewable energy sources (RES)'s to the economic, environmental, and social dimensions of sustainable development. Moreover, we add energy security as a possible fourth dimension into the analysis. For the sample size, we limit the countries members of the OECD and run generalized methods of moments for the period from 1995 to 2015. This method can produce efficient estimators under the problems of endogeneity, omitted-variable bias, measurement errors, and heteroscedastic residuals. According to the results, RES has a small reducing effect (-.007%) on output in the Cobb-Douglas production function for the economic dimension. We found that RES has a positive contribution to the environmental dimension and abates the level of carbon emission (-.093%). RES also confirms the inverted-U shape of environmental Kuznets curve. In the social dimension, RES improves human development and a 1% increase in RES consumption causes to .0045% increase in human development. In the last contribution, RES has a positive effect on sustainable energy supply security in the context of electricity generation (.032%). Although the effects of RES on the environment, social, and energy security are significant, they are limited. These limitations point to barriers that can be overcome over time. Our conclusions recommend that these effects might flourish with technical developments and political support in the long run. Furthermore, public awareness, rising income level, and economies of scale are also beneficial in this process. As a result, RES might be an excellent source for a sustainable future and development. Especially, RES might have remarkable contributions to the 7th, 11th, 12th, and 13th goals of sustainable development.

The effect of renewable energy sources on carbon dioxide emissions: Evaluating the role of governance, and ICT in Morocco

The increasing level of carbon emissions is one of the most serious concerns in human history facing in today's world. Different countries adopt different policies and approaches to mitigate climate change severity. The current study evaluates the effect of carbon emissions, renewable energy sources, ICT, governance, and GDP in Morocco employing a time-series dataset over the period of 1985–2020. In this paper, we utilized the dynamic ARDL simulations model to explore the association among carbon emissions, renewable energy sources, ICT, governance, and GDP. The ARDL bounds test reveals a long-run connection among the variables. The findings suggest that renewable energy sources (i.e. solar, wind, hydroelectric), ICT, and effective governance are the key indicators to reduce carbon emissions. In addition, we utilized the Granger causality test to probe a causal connection between the study variables. The outcomes have long-run implications for carbon emissions degradation and Morocco's policy towards the fight against climate change.

Correction: Alasali et al. Forecasting and Modelling the Uncertainty of Low Voltage Network Demand and the Effect of Renewable Energy Sources. Energies 2021, 14, 2151

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The moderating role of human capital and renewable energy in promoting economic development in G10 economies: Evidence from CUP-FM and CUP-BC methods

Economic development is attributed to higher energy consumption emerged from economic and industrial activities, whereas renewable energy is pronounced as the differentiating factor for achieving competitiveness among the economies and ensuring environmental sustainability. On the other hand, Human Capital plays the role of an interface between the inputs or resources consumed and the output generated; therefore, it can also derive economic development in a better way. Thus, this study explores the impact of human Capital, renewable energy, and the interaction of both in realizing higher economic development. For empirical analysis, we employed comparatively new panel estimation techniques “continuously updated fully modified” (Cup-FM) and “continuously updated bias-corrected” (Cup-BC) using a panel of G-10 countries. The overall results demonstrate that human Capital and renewable stimulate higher economic development. Manifestly, the interaction of both variables reports a more substantial impact on economic development, implying that human capital development is a stimulus to boost the positive effects of renewable energy sources on economic growth. Based on the findings, the stakeholders are recommended to invest in human Capital and renewable energy adoption.

Modelling the Potential Impacts of Nuclear Energy and Renewables in the Turkish Energy System

With heightening global concerns about the impacts of climate change, the debate around different carbon mitigation options is gaining momentum. A widespread argument is between those for and against utilizing nuclear energy as a low-carbon energy source. This debate is also relevant for Turkey, a country that is set to introduce nuclear energy to its electricity generation mix over the coming years. The purpose of the study is to assess the potential merits and drawbacks of the utilization of nuclear energy in the country versus the increased utilization of renewable energy sources. A fundamental merit order model is used for modeling the Turkish electricity market until 2025 under three scenarios. The comparative effects of renewable energy sources and nuclear energy are evaluated in terms of their impact on electricity generation costs, CO2 emissions and energy security. The results of the study show that the increased utilization of renewable energy has a more effective role in achieving the country’s energy targets in comparison to nuclear energy.

Spatial merit order effects of renewables in the Italian power exchange

Estimating the merit order effect of renewable energy sources provides key information inputs in several domains, notably in the design of green energy policies. Given the spatial nature of electricity supply and demand, it is important to disentangle the direct effect of renewables on zonal electricity prices from spatial spillovers. In this paper, we estimate spatial econometric models of the Italian zonal electricity prices, using IPEx daily average prices in the time window 2009–2015, for 6 market zones. The best specification is a spatial Durbin model including wind power, solar power, and hydropower production, as well as control variables. The model is estimated under different assumptions on the spatial-weighting matrix and in 3 sub-periods. Direct and indirect merit order effects are found stronger over time, especially for wind power; but the estimated merit order effect is smaller than in non-spatial models, suggesting that our analysis is capable of accounting for spatial spillovers.

Optimal energy management for multi-energy multi-microgrid networks considering carbon emission limitations

Multi-energy multi-microgrid (MMG) networks are considered as a promising form of energy systems that can integrate various energy resources and improve energy utilization efficiency. Carbon emission limitation, regarded as a significant factor in energy management, has received increasing attention in recent years. By taking into account both economic and environmental factors, MMG networks can offer a great opportunity to reduce operation costs and carbon emissions. In this paper, we propose an optimal energy management strategy for minimizing the operation cost of an MMG network, considering operation constraints and carbon emissions. The energy management strategy is designed to consist of a day-ahead phase and an intra-day phase to overcome the uncertainty effects of renewable energy sources (RESs) generation and load demands. We first present a day-ahead scheduling strategy for the MMG network, in which microgrids operate in a distributed manner and share electricity while preserving their privacy. We then present an intra-day scheduling strategy for each microgrid, in which the operation costs and penalty costs caused by the adjustment of energy devices and energy procurement are minimized sequentially using a rolling horizon method. Simulation results demonstrate the effectiveness of the proposed energy management strategy in lowering operation costs and carbon emissions.