Consumption Of Renewable Energy Sources Research Articles

Impact of Key Drivers on Energy Intensity and GHG Emissions in Manufacturing in the Baltic States

The improvement in energy efficiency (EE) and increasing consumption of renewable energy sources (RES) in manufacturing play an important role in pursuing sustainable development in the Baltic States and contribute to the transition to a low-carbon economy. This paper presents the results of a detailed analysis of the channel through which EE, along with structural activity changes, passes energy intensity and total energy savings and in combination with other key drivers results in reductions in greenhouse gas (GHG) emissions in manufacturing in Estonia, Latvia, and Lithuania during the period 2010–2020, taking into account the role of transformations in the energy and climate framework of the European Union (EU). The Fisher Ideal Index, the Kaya identity, the Logarithmic Mean Divisia Index (LMDI), and comparative analysis methods are used. The results of the impact analysis of key drivers on energy intensity showed different contributions towards improvements in EE and structural activity changes to changes in energy intensity in manufacturing, which decreased by 53.1% in Estonia, by 30.5% in Lithuania, and by 16.5% in Latvia. The dominant role of EE improvements on total energy savings is identified. The results of the GHG decomposition analysis showed that because of improvements in energy intensity, reductions in the share of fossil fuels, and increases in labour productivity, number of employees, and emissions intensity, the GHG emissions decreased by 35.5% in Estonia, 40.4% in Latvia, and 8.1% in Lithuania. The results confirm the need for new policies and the implementation of relevant commitments to save energy and increase the contribution of RES in all three countries.

RETRACTED: An empirical investigation of the impact of renewable and non-renewable energy consumption and economic growth on climate change, evidence from emerging Asian countries

One of the greatest challenges facing humanity in the current millennium is the need to mitigate climate change, and one of the most viable options to overcome this challenge is to invest in renewable energy. The study dynamically examines the impact of renewable and non-renewable energy consumption and economic growth on climate change, using Augmented Mean Group (AMG) technique in emerging Asian countries during the period 1975–2020. The estimated results show that the consumption of renewable energy sources significantly mitigates climate change, while the consumption of non-renewable energy sources significantly contributes to climate change. Furthermore, economic growth, investment in transport infrastructure, and urbanization significantly accelerate climate change in specific emerging Asian countries. The results further demonstrate the validity of the inverted U-shaped EKC hypothesis in emerging Asian economies. Country-specific analysis results using AMG estimates shows that renewable energy consumption reduces climate change for all specific emerging Asian countries. However, the consumption of non-renewable energy sources and investments in transport infrastructure have significant incremental impacts on climate change in all countries. Urbanization contributes significantly to climate change, with the exception of Japan, which does not have any significant impact on climate change. The significant progressive effect of GDP and the significant adverse impact of GDP2 on climate change confirm the validity of the inverted U-shaped EKC hypothesis in India, China, Japan, and South Korea. Moreover, the Dumitrescu and Hurlin causality test confirmed a pairwise causal relationship between non-renewable energy consumption and GDP, supporting the feedback hypothesis. According to the empirical analysis of this study, the best strategy for climate change mitigation in specific emerging countries in Asia is to transition from non-renewable energy to renewable energy.

The Significance of FDI Inflow and Renewable Energy Consumption in Mitigating Environmental Degradation in Somalia

This study explores the impact of foreign direct investment (FDI), renewable energy, gross capital formation, population growth, gross domestic product (GDP), and the square of GDP on carbon dioxide (CO2) emissions in Somalia between 1990 and 2019. To investigate the short- and long-run elasticity of environmental degradation and the other variables, the autoregressive distributed lag (ARDL) model is employed. In Somalia, the long-run coefficients of the ARDL model indicate that renewable energy contributes negatively to environmental degradation. At the same time, domestic investment and population growth undermine the quality of the environment. Furthermore, the FMOLS results validate the existence of EKC in Somalia. The Granger causality test is also applied to investigate the causal relationship between the variables. Despite this, there was no evidence that FDI and renewable energy are causally related to environmental degradation. Based on our empirical assessment, the Somali government should encourage foreign direct investment, especially in technology-intensive and environmentally friendly industries, and pay increased attention to the improvement and consumption of renewable energy sources.

Predictive Multimodal Deep Learning-Based Sustainable Renewable and Non-Renewable Energy Utilization

Recently, renewable energy (RE) has become popular due to its benefits, such as being inexpensive, low-carbon, ecologically friendly, steady, and reliable. The RE sources are gradually combined with non-renewable energy (NRE) sources into electric grids to satisfy energy demands. Since energy utilization is highly related to national energy policy, energy prediction using artificial intelligence (AI) and deep learning (DL) based models can be employed for energy prediction on RE and NRE power resources. Predicting energy consumption of RE and NRE sources using effective models becomes necessary. With this motivation, this study presents a new multimodal fusion-based predictive tool for energy consumption prediction (MDLFM-ECP) of RE and NRE power sources. Actual data may influence the prediction performance of the results in prediction approaches. The proposed MDLFM-ECP technique involves pre-processing, fusion-based prediction, and hyperparameter optimization. In addition, the MDLFM-ECP technique involves the fusion of four deep learning (DL) models, namely long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), deep belief network (DBN), and gated recurrent unit (GRU). Moreover, the chaotic cat swarm optimization (CCSO) algorithm is applied to tune the hyperparameters of the DL models. The design of the CCSO algorithm for optimal hyperparameter tuning of the DL models, showing the novelty of the work. A series of simulations took place to validate the superior performance of the proposed method, and the simulation outcome emphasized the improved results of the MDLFM-ECP technique over the recent approaches with minimum overall mean absolute percentage error of 3.58%.

Threshold effects of renewable energy consumption by source in U.S. economy

• We established a threshold model for data from REC by source in U.S. • Nonlinear relationship b/w REC by source and GDP. • The effect of REC on GDP depends REC by source used. • Effect is positive if U.S. use REC by source above a threshold. • Effect is negative if U.S. use REC by source below a threshold. With the climate challenges and the depletion of fossil resources, the renewable energy option seems to be a wise choice; this renews the debate on the relationship between renewable energy sources consumption and economic growth. This study relies on a threshold effects regression model to explore and evaluate the non-linear relationship between the series in the United States during the period 1984Q1–2021Q3. Using the threshold detection method proposed by Hansen and Seo (2002), the results of this method show that the renewable energy sources consumption/GDP relationship is non-linear. They also reveal, for all the different sources, an optimal renewable energy sources consumption/GDP threshold of 5.535; 2.715; 1.988 and 8.925% for BIO, GEO, Solar and HPower, respectively. The results indicate the presence of mixed directions of causality between the renewable energy sources consumption and GDP, using the Threshold Vector Error Correction model (TVECM). The findings of this paper suggest that if the United States aim to realize positive economic growth from their investment to renewable energy, they need to surpass a certain threshold of renewable energy sources consumption.

The Economic Value of Natural Resources and Its Implications for Pakistan’s Economic Growth

Natural resources and ecological services provide the foundation for manufactured capital, increasing public financing and decreasing inequality by diversifying the economy. The exploitation of natural resources is frequently the backbone of economic stability in developing and middle-income nations. As a result of their importance, natural resources need vigilant and long-term management. Recent research has tested two hypotheses, the natural resource blessing hypothesis and the natural resource curse hypothesis, on the impact of a country’s natural resources on its economy. This research is an essential contribution to the growing body of work that attempts to quantify natural resource endowments’ role in national economic growth. Investigations focus on Pakistan and span the years 1975 through 2020. Robust Least Square (RLS) estimations show that coal rents, energy use, inbound FDI, and oil rents contribute to a country’s economic growth. While consumption of renewable energy sources and industrial value-added have a detrimental effect. Natural resources, foreign direct investment, energy consumption, and industrial ecology are predicted to significantly impact economic growth during the next decade, according to the Impulse Response Function (IRF) and the Variance Decomposition Analysis (VDA). The findings may provide helpful information for academic and governmental institutions to develop natural resource management policies for sustainable development.

Optimal Microgrid System Operating Strategy Considering Variable Wind Power Outputs and the Cooperative Game among Subsystem Operators

In recent years, the microgrid system (MGS) has become an important method for the consumption of renewable energy sources (RES). In the actual operation process, the uncertainties of RES add to the complexity of the MGS operation. Furthermore, the MGS is often operated by multiple subsystem operators. The benefit distribution among subsystem operators is an important factor affecting the overall stable operation of the MGS. In order to resist the interference of the above factors, a two-stage optimization method is proposed in this paper, which includes a bi-level robust optimization (BRO) model in the overall scheduling stage of the MGS and a nucleolus-based cooperative game (NCG) model in the internal cost allocation stage among the subsystem operators. The simulations demonstrated the following outcomes: (1) the P2G device can reduce the operating cost of the MGS by converting electricity into natural gas when the electricity price is low; (2) the two-stage optimization method can ensure the stable operation of the MGS by resisting the disturbance of uncertain wind power outputs in the overall scheduling stage and realizing a reasonable cost allocation among the subsystem operators in the internal cost allocation stage.

Hybrid AC/DC-coupled charging station architecture with comprehensive hierarchical control for optimal economical operation and load variance minimization

This paper introduced a novel hybrid AC/DC-coupled charging station architecture and corresponding hierarchical control strategy. The core element of the architecture is an integrated interlinking converter (ILC) named the energy routing unit (ERU). The ERU features multiple conversion stages, dedicated plug-and-play interfaces, and varied operation functionalities. The dual inputs of utility sources enhance the reliability of the power supply. The contained scalable charging module facilitates the DC fast charging via DC grids directly, and the traditional AC slow charging is also accommodated in this architecture. Regarding the architecture, a comprehensive hierarchical control strategy containing the local-level short-timescale transient control and upper-level long-timescale optimal power scheduling is proposed. The multi-objective optimization concerning the optimal economical operation and minimum load variance is incorporated into the upper-level power flow control. The detailed simulation cases demonstrate that the stable operation of the proposed architecture could be realized, and the desirable economical operation and low peak-to-valley load variance are to be implemented simultaneously. The enabled vehicle-to-vehicle (V2V) power coordination achieves mutual power support between AC and DC subgrids and increases the local consumption of renewable energy sources effectively.

Advancements in energy storage technologies for smart grid development

<span>In the modern world, the consumption of oil, coal natural gas, and nuclear energy has been causing by a serious environmental problem and an ongoing energy crisis. The generation and consumption of renewable energy sources (RESs) such as solar and wind tidal, can resolve the problem but the nature of the RESs is fluctuating and intermitted. This evolution brings a lot of challenges in the management of electrical grids. The paper reviewed the advancements in energy storage technologies for the development of a smart grid (SG). More attention was paid to the classification of energy storage technologies based on the form of energy storage and based on the form of discharge duration. The evaluation criteria for the energy storage technologies have been carried out based on technological dimensions such as storage capacity, efficiency, response time, energy density, and power density, the economic dimension such as input cost and economic benefit; and the environmental dimension such as emission and stress on ecosystem, social demission such as job creation and social acceptance were also presented in this paper.</span>

Hierarchical Scheduling Control Method for Cascade Hydro-PV-Pumped Storage Generation System

High photovoltaic penetration in a power system has significantly challenged its safety and economic operation. To use the complementary characteristics of various renewable energy sources (RESs) fully, a novel hierarchical scheduling control (HSC) method is presented to accommodate the variability and uncertainty of a cascade hydro-PV-pumped storage (CH-PV-PS) generation system. Considering the optimization functions and execution requirements of the CH-PV-PS system, the HSC method is divided into two layers: the dynamic optimization layer and the static optimization layer. The static optimization layer focuses on the economy of the CH-PV-PS system, and the dynamic optimization layer focuses on the safety of the CH-PV-PS system. In the first layer, that is, the static optimization layer, the objectives of the day-ahead and hour-ahead schedules are established, and a heuristic algorithm is combined with a linear programming algorithm to optimize the energy allocation. Considering the uncertainty of the PV power output and hour-ahead load, a real-time schedule is established in the second layer; that is, in the second layer, the dynamic optimization layer, real-time scheduling and prediction of active output are established. Model predictive control methods are introduced to correct for prediction bias at different time scales in order to fully utilize the control capability of hydropower generation. A CH-PV-PS real-world system in Southwest China is chosen as a case study. In the three scenarios, where only PV fluctuations are considered, the simulation results reveal that, compared with the traditional open-loop optimized and hierarchical open-loop optimization methods, the HSC method reduces the average relative deviation of PV and increases the system economics. After a large amount of RESs are connected to the power grid, the HSC method provides a solution for improving the consumption of RESs.

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.

Financial inclusion and its influence on renewable energy consumption-environmental performance: the role of ICTs in China

Financial inclusion means that individuals and businesses can easily avail financial goods and services at an affordable cost. It is widely recognized that financial inclusion can help preserve the environment by increasing the consumption of renewable energy sources. Hence, our basic aim is to investigate whether financial inclusion has any effect on renewable energy consumption and environmental quality in China. To get the estimates of the variables, we have preferred the ARDL model. The estimates of the model confirm that a rise in the number of ATMs and total insurance has a positive impact on renewable energy consumption in China in the long run. Conversely, an increase in the number of ATMs and total insurance negatively affects CO2 emissions in China. In general, we can say that financial inclusion increases renewable energy consumption and reduces CO2 emissions in China. Therefore, by using financial inclusion, policymakers should try to divert the resources towards environmentally friendly consumption and production activities.

A novel rolling optimization strategy considering grid-connected power fluctuations smoothing for renewable energy microgrids

The rise of microgrids provides an effective solution to the problem of local consumption of renewable energy sources. However, the power fluctuations are the crucial issue for the widespread adoption of the grid-connected microgrid with renewable energy sources. We aim to economically and locally solve the problem of grid-connected power fluctuations of microgrid. In this paper, a novel rolling optimization strategy considering grid-connected power fluctuations smoothing for microgrids is provided. Firstly, the mathematical model of the microgrid is described, which contains the grid-connected power limits and supercapacitor-battery hybrid energy storage system. Then, a priority-based smoothing method of power fluctuations is proposed for the first time. As a flexible load, the heating/cooling load is used as virtual energy storage to participate in power regulation. Finally, the rolling optimization strategy integrated with the energy trigger mechanism is designed to achieve the operation optimization. The objectives of this paper are to help the microgrids improve grid-connection friendliness and minimize the daily operating costs that include fluctuation penalties. Simulation results on different scenarios for a grid-connected microgrid show that the novel rolling optimization strategy has better performance in any scenario. Compared with the traditional strategy, the total operating costs of the proposed strategy can save 5.67% for a given scenario. We can conclude that the proposed rolling optimization strategy can effectively reduce cost payment and meet the requirement of grid-connected power fluctuations smoothing.

Utilization of Renewable Energy Sources in Road Transport in EU Countries—TOPSIS Results

The primary aim of this study was to assess and compare EU countries in terms of the use of renewable energy sources in road transport. The following research tasks were undertaken to realize this aim: (1) a review of the literature concerning the negative externalities in road transport, the concept of sustainable development, and legal regulations referring to the utilization of renewable energy sources; (2) presentation of changes in energy consumption (both traditional and renewable) in road transport in EU countries in the years 2008–2019; and (3) identification of leaders among the EU countries in terms of consumption of renewable energy sources in road transport. The aim and tasks were realized using the literature review and TOPSIS method as well as descriptive, tabular, and graphic methods. The analysis was conducted for 28 EU countries according to the status for 2019. The period of 2008–2019 was investigated. Sources of materials included literature on the subject and Eurostat data. Although renewable energy sources accounted for as little as 6% of total energy consumption in road transport in EU countries in 2019, this is a significant topical issue. It results from the direction in which changes need to be implemented in terms of energy generation in this area of human activity. It turned out that blended biodiesel and blended biogasoline were the most commonly used fuels originating from renewable sources. The application of the TOPSIS method resulted in the identification of five groups of EU member countries, which differed in terms of the degree of utilization of renewable energy sources in road transport. Luxemburg, Sweden, and Austria were leaders in this respect. In turn, Malta, Estonia, and Croatia were characterized by very low consumption of renewable energy. The greatest progress in the utilization of renewable energy sources in road transport was recorded in Sweden, Finland, and Bulgaria (changes in the relative closeness to the ideal solution from 0.15 to 0.27), while the greatest reduction in relation to other countries was observed in Austria, Germany, and Lithuania (changes from −0.35 to −0.22).

Capacity configuration optimization and analysis for multi-energy complementary microgrid in hydropower station considering the renewable energy accommodation

Aiming at the problems of large short-term fluctuation, strong randomness and difficulty to consume of renewable energy generation, it is an important way to integrate abundant wind and photovoltaic (PV) power into hydropower stations to promote the consumption of renewable energy sources (RES). A hydro-wind-PV and energy storage multi-energy complementary microgrid (MECM) model is proposed to meet the demand of load supply and RES consumption. Firstly, according to the characteristics of load and resource endowment, the MECM is established in a hydropower station. Secondly, according to the two different objectives of load self-sufficiency and RES consumption, the mathematical model for the capacity configuration optimization of MECM was proposed. Finally, combined with the practical case study, the effectiveness and practicability of this scheme are verified, and different configuration schemes are discussed based on different objectives.

Relationship of renewable energy consumption to economic, environmental and institutional factors in Europe

Challenges caused by global climate change arise several environmental, social, and energy production issues. These problems firstly concern interest of resource extraction countries, triggering inter-fuel competition in both directions supply and consumption of energy resources. Moreover, significantly increased green agenda leads countries to foster shifting to green energy production and discovering factors of most influential on the acceleration of RES consumption. The paper focuses on the impact assessment of economic, environmental and institutional factors of the country development on the future consumption of renewable energy sources (RES). To achieve the purpose of the study a panel data analysis method was used. The analysis was conducted for 41 European countries for 1995–2018, with countries being divided into members of Organization for Economic Co-Operation and Development (OECD)/non-OECD and Extractive/non-Extractive. Four hypotheses were tested under the research: (1) Developing countries are characterized by the negative impact of CO2 emissions on RES consumption, while developed countries — the opposite; (2) Non-RES consumption reflects inter-fuel competition, expressed in a negative relationship with the RES; (3) Prices increase for non-RES contributes to growth of RES consumption; (4) Institutional factors reflect the level of ”market freedom and mobility” of the country and contribute to the development of RES. The authors confirmed all hypothesizes and showed that economic, particularly GDP, and institutional factors had the greatest impact on all countries’ RES consumption, while the environmental aspect is weakly significant for non-extractive countries. Consumption of fossil resources had a negative impact and confirmed the presence of inter-fuel competition.

The Consumption of Renewable Energy Sources (RES) by the European Union Households between 2004 and 2019

The paper provides the analysis of fuel and energy transition in households sector and its sustainable development in the period 2004–2019. The main purpose of the paper is to determine the development trends in the use of renewable energy sources (RES) in the EU countries household sector in 2004–2019, to recognize the state of development and functioning of the studied area as well as to indicate their successes and shortcomings in observed reality. The article employs the results of Energy balance sheets from Eurostat. The research entity were households from 28 European Union countries, with particular emphasis on households from Poland and selected neighboring countries. The research subjects there were different sources of renewable energy used by households, i.e., solar thermal system, geothermal technologies, primary solid biofuels, charcoal, biogases, blended biogasoline, blended biodiesels, ambient heat (heat pumps). To achieve the research objective a number of statistical measures ands methods, including cluster analysis and linear trend indicator applied. In the analyzed 16 years, an absolute and relative increase in the use of RES in the household sector was noticed. Taking into account the specificity of using RES in households, 6 clusters of countries were distinguished. In Poland, it was noted that there was a significant increase in the use of RES in households, with stagnation in the use of non-renewable energy sources, such as, for example, hard coal.

Do energy security and environmental quality contribute to renewable energy? The role of trade openness and energy use in North African countries

No considerable evidence is available in literature review regarding the drivers of renewable energy in North African countries. We attempt to fill this gap by empirically exploring the relationships among consumption of renewable energy sources, carbon dioxide emissions, economic growth, energy security, energy use, trade openness, foreign direct investment and population in North African countries mainly Egypt, Morocco and Tunisia from 1971 to 2014. To attain this objective, we use Panel PMG ARDL and Granger causality approaches to examine the co-integration and causality.Findings reveal that economic growth, emissions of carbon dioxide, trade openness and foreign direct investment trigger renewable energy which stress why policymakers can no longer overlook these variables while designing policies aiming at accelerating the shift towards renewable energy. On the contrary, energy security, energy use and population hamper it. Moreover, bi-directional causal relation between energy security and economic progress exists and energy security, direct foreign investments and deterioration in the environment cause renewable energy. In the light of these findings crucial policy implications concerning enhancing renewable energy technologies, encouraging green investment and promoting energy efficiency can be proposed.

ESTIMATING ROLE OF GREEN FINANCING ON ENERGY SECURITY, ECONOMIC AND ENVIRONMENTAL INTEGRATION OF BRI MEMBER COUNTRIES

China’s Belt and Road Initiative (BRI) developed a system of interaction with the member countries to uplift economic and environmental integration. Through BRI, these countries are now developing in the field of financial management, energy and environment. This raised the importance to test nexus between energy, finance and environment-related constructs to present the empirical significance with policy suggestions. Therefore, considering the SDG number 7 for sustainable and reliable energy system, recent investigation attempted to determine that how green financing raise energy efficiency, and, to what extent economic and environmental integration act as a catalyst to enhance sustainability and reliability in energy systems of BRI member countries. For empirical analysis, study used the data from 2005–2018. The results have shown a significant variation in energy financing patterns, renewable energy sources consumption and carbon emission trends in BRI member nations. Moreover, the Probit regression analysis confirmed this variation between energy efficiency, financing patterns and carbon emission. Moreover, Human Development Index (HDI) and public financing in energy sector have shown a limited role in developing energy efficiency, which presented the room for private investment through green financing for energy efficiency maximization and this proved as significant in study context. This study also presented policy guidelines for key stakeholders.

Optimal Planning and Operation of a Residential Energy Community under Shared Electricity Incentives

Energy communities (ECs) are becoming increasingly common entities in power distribution networks. To promote local consumption of renewable energy sources, governments are supporting members of ECs with strong incentives on shared electricity. This policy encourages investments in the residential sector for building retrofit interventions and technical equipment renovations. In this paper, a general EC is modeled as an energy hub, which is deemed as a multi-energy system where different energy carriers are converted or stored to meet the building energy needs. Following the standardized matrix modeling approach, this paper introduces a novel methodology that aims at jointly identifying both optimal investments (planning) and optimal management strategies (operation) to supply the EC’s energy demand in the most convenient way under the current economic framework and policies. Optimal planning and operating results of five refurbishment cases for a real multi-family building are found and discussed, both in terms of overall cost and environmental impact. Simulation results verify that investing in building thermal efficiency leads to progressive electrification of end uses. It is demonstrated that the combination of improvements on building envelope thermal performances, photovoltaic (PV) generation, and heat pump results to be the most convenient refurbishment investment, allowing a 28% overall cost reduction compared to the benchmark scenario. Furthermore, incentives on shared electricity prove to stimulate higher renewable energy source (RES) penetration, reaching a significant reduction of emissions due to decreased net energy import.