The study investigates the long-run and causal interaction between, renewable energy consumption, nonrenewable energy consumption, and economic growth in a carbon function. The current study ...incorporates natural resources rent to the model as an additional variable. Empirical evidence is based on a balanced panel data between annual periods of 1996–2014 for selected EU-16 countries. The Kao test reveals a cointegration between carbon dioxide emissions, economic growth, natural resources rent, renewable, and nonrenewable energy consumption. The Panel Pooled Mean Group-Autoregressive Auto regressive distributive lag model (PMG-ARDL) suggests a positive significant relationship between the countries' natural resource rent and CO2 emissions in the long-run. Implying that the overdependence on natural resource rent affects environmental sustainability of the panel countries if conservation and management options are ignored. Our study affirms that nonrenewable energy consumption and economic growth increase carbon emission flaring while renewable energy consumption declines CO2 emissions. The panel causality analysis reveals a feedback mechanism between economic growth, renewable, and nonrenewable energy consumption. We further observed a feedback causality between natural resources rent and economic growth. Effective policy implications could be drawn toward modern and environmentally friendly energy sources, especially in attaining the Sustainable Development Goals.
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•Renewable energy consumption improves environmental quality in 16 EU countries.•Feedback causality observed between natural resources rent and economic growth.•Long-term risk of natural resource rent affecting environmental sustainability.•Economic growth influences carbon dioxide emissions in EU-16 countries.•Fossil fuels exert more distortion on environmental sustainability.
The Republic of Ghana aims to develop and utilise renewable energy and energy efficiency technologies to achieve a 10% penetration of national electricity production by 2020. The government also aims ...to achieve a 100% national electrification with renewable energy identified as the catalyst for achieving this policy goal. The situation however is, as of December 2017, Ghana has been able to achieve a 0.5% penetration rate of electricity from renewable energy sources in its total generation mix. This paper argues that Ghana is unable to reach its renewable energy target of 10% by 2020 given that it needs to integrate 9.5% of renewables from 2018 to 2020 whiles it has only been able to achieve 0.5% penetration rate since 2006. Legal and regulatory issues such as lack of legislative instruments by regulatory agencies incumbent upon achieving the renewable energy policy target, lack of independence of institution structure and the lack of regulatory assessment are some of the key reasons behind this argument. The implication of these issues is that, investors lose confidence in the government's ability to maintain and achieve both current and future renewable energy policy goals. Investors become uncertain and this leads to underinvestment in renewable projects and subsequently, failure in achieving renewable energy targets.
This open access book presents detailed pathways to achieve 100% renewable energy by 2050, globally and across ten geographical regions. Based on state-of-the-art scenario modelling, it provides the ...vital missing link between renewable energy targets and the measures needed to achieve them. Bringing together the latest research in climate science, renewable energy technology, employment and resource impacts, the book breaks new ground by covering all the elements essential to achieving the ambitious climate mitigation targets set out in the Paris Climate Agreement. For example, sectoral implementation pathways, with special emphasis on differences between developed and developing countries and regional conditions, provide tools to implement the scenarios globally and domestically. Non-energy greenhouse gas mitigation scenarios define a sustainable pathway for land-use change and the agricultural sector. Furthermore, results of the impact of the scenarios on employment and mineral and resource requirements provide vital insight on economic and resource management implications. The book clearly demonstrates that the goals of the Paris Agreement are achievable and feasible with current technology and are beneficial in economic and employment terms. It is essential reading for anyone with responsibility for implementing renewable energy or climate targets internationally or domestically, including climate policy negotiators, policy-makers at all levels of government, businesses with renewable energy commitments, researchers and the renewable energy industry.
This study explored the effects of economic growth (EG), renewable energy consumption (REC) and non-renewable energy consumption (NREC) on CO2 emissions (CE) and tested the Environmental Kuznets ...Curve (EKC) hypothesis at the regional levels in China. The study was based on a balanced provincial panel dataset for the period of 1995–2012. The empirical results suggested that the inverted U-shaped EKC hypothesis was not supported in the central and western regions and was barely supported in the eastern region. NREC was found to have a positive effect on CE, although this varied across the three regions, with the greatest impact being in the central region, followed by the western and eastern regions. REC had a negative impact on CE in the eastern and western regions, while the impact was weak and statistically insignificant in the central region. Furthermore, we found that REC had no significant impact on the EKC hypothesis in the three regions. Panel causality tests showed that the direction of causality in both short and long runs was mixed among regions. There were bidirectional causalities between REC, CE, and EG in the long-term for the three regions.
•Examine the relationships among CO2 emissions, economic growth, renewable and non-renewable energy.•The inverted U-shaped EKC hypothesis isn’t supported in the central and western regions.•The impact of renewable energy on the CO2 emissions varies across regions.•There are bidirectional causalities between renewable energy, CO2 emissions and economic growth in the three regions.
The energy sector has become the largest contributor to greenhouse gas (GHG) emissions. Among these GHG emissions, most threatening is CO
emission which comes from the consumption of fossil fuels. ...This empirical work analyzes the roles of renewable energy consumption and non-renewable energy consumption in CO
emissions in Pakistan. The empirical evidence is based on an auto-regressive distributive lag (ARDL) model of data from 1970 to 2016. The disaggregate analysis reveals that renewable energy consumption has an insignificant impact on CO
emission in Pakistan and that, in the non-renewable energy model, natural gas and coal are the main contributors to the level of pollution in Pakistan. Economic growth positively contributes to CO
emission in the renewable energy model but not in the non-renewable energy model. Policies that emphasize the contribution of renewable energy to economic growth and that add more clean energy into the energy mix are suggested.
Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, ...turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights
Achieving high renewable energy penetrated power systems requires considerable operational flexibility to hedge the variability and uncertainty of variable renewable energy (VRE) generation. Compared ...with VRE sources, concentrating solar power (CSP) is an emerging controllable renewable generation technique that utilizes solar thermal power to generate electricity. The operational dispatchability of CSP would contribute to the power system transition toward high renewable penetration. In this paper, we explore how the generation portfolio will change toward high renewable energy penetrations, how much cost is involved, and what role CSP will play in realizing a high renewable energy penetrated power system. This study relies on a stochastic two-stage generation and transmission expansion planning model with CSP plants. The model captures the uncertainty and variability of renewable generation and the flexibility limits of thermal plants. With the target of achieving a renewable-dominated minimum-cost system with an expected renewable energy penetration level, the investments of both generation and transmission facilities are optimized. A case study on IEEE test systems with renewable technology cost data in 2050 is performed to analyze the value of CSP toward high renewable energy penetrated power systems.
The aim of this study is to investigate the relative performance of renewable and non-renewable energy consumption on economic growth in 17 emerging economies. For this purpose, the annual data from ...1980 to 2012 is examined using with bootstrap panel causality that allows both cross-section dependency and country specific heterogeneity across countries. In the case of renewable energy consumption, the results reveal that the growth hypothesis is confirmed only for Peru; the conservation hypothesis is supported for Colombia and Thailand; the feedback hypothesis is found for Greece and South Korea and the neutrality hypothesis is valid for the other 12 emerging economies. In the case of non-renewable energy consumption, the growth hypothesis is found for China, Colombia, Mexico and Philippines; the conservation hypothesis is confirmed for Egypt, Peru and Portugal; the feedback hypothesis is supported only for Turkey and the neutrality hypothesis is valid for the other 9 emerging economies.
•We compare the economic performances of renewable and nonrenewable energy use.•Renewable energy causes economic growth in Peru, Greece and South Korea.•Nonrenewable energy causes growth in China, Colombia, Mexico Philippines, Turkey.
There are a lot of studies that show the legitimacy of subsidizing renewable energy; however, some mechanisms are defective, and there are problems with the appropriate allocation of funds. ...Therefore, this paper aims to look at the situation of allocating funds to photovoltaics (PV) micro-installations in Poland through the “My Electricity” program. The article presents the results of analyses aimed at identifying inequalities between provinces in the use of funds available under the “My Electricity” program and verifying whether these inequalities are getting worse and whether the intensity of support should not be territorially conditioned in terms of maximization an electricity production. As part of two editions of the “My Electricity” program (until 1 August 2020), over 64,000 PV micro-installations were created with an average power of approximately 5.7 kWp. The total installed PV capacity was 367.1 MWp (1st edition: 159.3 MWp, 2nd edition: 207.8 MWp). Financial resources (as a whole), in the second edition of “My Electricity” program, were distributed better than in the first edition. In the first edition, as much as 7.60% of funds were allocated inefficiently; in the second edition, it was only 3.88%. Allocation surpluses occur in provinces where the average disposable income is low and where there are a small number of households. There is a potential to introduce a territorial project selection criteria. The analysis shows that the criteria should promote provinces with higher disposable income and a larger number of households.
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