Renewable Energy Electricity Generation Research Articles

The Possibility and Improvement Directions of Achieving the Paris Agreement Goals from the Perspective of Climate Policy

Currently, climate change and global warming have significantly impacted human life. In the context of sustainable development, achieving the goals of the Paris Agreement is both urgent and complex. This paper presents a comprehensive review of climate policies worldwide. Based on the global comprehensive climate policy database that we constructed and using global panel data from 1990 to 2019, we predicted the emission reduction due to climate policies using trend and fixed-effects models to identify areas for improvement. The research findings indicate that there is a considerable gap between current climate policies and the targets set by the Paris Agreement, both in terms of quantity and effectiveness. Economic growth and primary energy consumption contribute to increased greenhouse gas emissions, while increasing the proportion of renewable energy in electricity generation and implementing climate policies have the effect of reducing greenhouse gas emissions. Relying solely on increasing the quantity or effectiveness of policies would require an increase of 15–30 times the levels seen before 2019 to achieve the 2 °C warming target of the Paris Agreement. However, simultaneously increasing the number of policy implementations and enhancing their effectiveness would only require about a fourfold increase from the levels seen before 2019. Additionally, the results of the study on national heterogeneity demonstrate significant differences in policy effectiveness among countries, indicating substantial potential for emission reduction. Furthermore, the analysis of policy legal enforceability shows that hard law policies outperform soft law policies, suggesting that increasing the implementation of hard law policies can more effectively reduce emissions.

A new information priority grey prediction model for forecasting wind electricity generation with targeted regional hierarchy

Amidst the global transition to renewable energy electricity generation, this study addresses the need for improved wind electricity generation forecasting, which is pivotal in optimizing energy strategies and meeting sustainability targets. The research introduces an innovative adaptation of the grey prediction methods, named UNAGO-GM (1, 1), which is enhanced by the unified new-information priority accumulating generation operator (UNAGO) that emphasizes more recent data. This advanced model significantly improves the model's adaptability and accuracy in forecasting wind electricity generation within the regional hierarchy. To demonstrate the proposed model’s superior forecasting efficacy, the comparative experiments are conducted in the hierarchical forecasting fashion across national, regional, and global levels by contrasting UNAGO-GM (1, 1) with prevailing benchmarks like ARIMA and LSTM. The results indicate UNAGO-GM (1, 1)’ s highest forecasting accuracy and universality, with 54.07% and 156.48% improvement rates concerning MAPEs and RMSEs across all benchmarks and forecasting levels. Furthermore, UNAGO-GM (1, 1)’s output stability is validated through the robustness tests applying Monte Carlo simulations for the intelligent algorithm stability and matrix perturbation analyses. In conclusion, the novel UNAGO-GM (1, 1) model represents a significant breakthrough in renewable energy forecasting, providing precise and adaptable predictions essential for strategic planning and policy formulation in the transition towards sustainable energy sources.

Reinvestigating the EKC hypothesis: Does renewable energy in power generation reduce carbon emissions and ecological footprint?

For a developing nation such as Malaysia with a significant reliance on fossil fuels for electricity, understanding the environmental consequences of this dependency is crucial. Thus, this study utilizes the Autoregressive Distributed Lag (ARDL) method to explore the impact of electricity intensity (EINT), renewable energy in electricity generation (ERE), and gross domestic product (GDP) on Malaysia's environmental quality, from 1985 to 2020. By using carbon emissions (CO2 emissions) and ecological footprint (EF) as proxies, the study finds a significant long-run impact of these factors on environmental degradation. Notably, the study also observed an inverted U-shaped relationship between GDP and environmental degradation, validating the existence of Environmental Kuznets Curve (EKC) hypothesis. The findings also imply that while electricity intensity is associated with increased emissions, the use of renewable energy (RE) sources for electricity generation may contribute to emission reduction. But the results for both variables show reversal signs on EF. The study's adoption of the fully ordinary least square (FMOLS) method reinforces the same results, thus, justifying the cointegrating relationship between studied variables. Drawing from these outcomes, the study advocates for a comprehensive approach to renewable energy management, emphasizing both its utilization and waste in order to improve ecological footprint. Moreover, the pressing need to enact legislation on energy efficiency and conservation is crucial in ensuring decoupling and securing sustainable development in Malaysia.

Dynamic effect of disaggregated level electricity generation on residential carbon emissions: Daily inference from the largest EU economies

This study examines the dynamic effects of electricity generation (EG) on CO2 emissions from the residential sector. The study focuses on the EU-4 countries (Germany, Spain, France, and Italy), considers residential CO2 emissions as the dependent variable, and includes disaggregated level fossil and renewable EG as explanatory variables. In this context, the study runs nonlinear quantile-on-quantile (QQ) regression and Granger causality in quantiles (GQ) as the main models with daily data from January 2, 2019, to March 10, 2023, while quantile regression (QR) is used for robustness check. The findings present that in terms of CO2 emissions: (i) EG from coal, natural gas, and oil has a stimulating effect at higher quantiles in all countries; (ii) EG from hydro has an increasing effect at higher quantiles, while it has a decreasing effect at lower and middle quantiles in all countries except France; (iii) EG from solar has a dampening effect at higher quantiles in all countries except France; (iv) EG from wind has a declining effect at higher quantiles in both Spain and France; (v) both fossil and renewable energy EG have a causal effect on residential sector CO2 emissions at the disaggregated level except at some quantiles. Overall, the effect size and the causal effect of EG on CO2 emissions change for quantiles, countries, and EG sources. Therefore, the study proposes to rely on the specific EG sources for Germany and Italy (solar energy), Spain, and France (wind energy) to mitigate climate change by reducing residential CO2 emissions.

Optimum Design on Integration Biogas into Fuel Cell System in Malaysia: Economic and Environmental Aspect

Transition to renewable energy in electricity generation need a serious study in variety of issues. Environment and economic perspective become the vital issue that need to study in local condition for penetration new concept of energy resources. Feeding a biogas into the fuel cell system seems an attractive way to less dependent on fossil fuel-based electricity generation. This study aims to optimize the plant location based on two aspect environment and economic. Capacitated Plant Location Model (CAPLOC MODEL) were used in determine the optimized location of the plant. The optimum design of power plant in Sarawak solely generated 847.91 MW and Pahang about 604.26 MW. Hopefully, the outcome of the study can provide the information for stakeholder in choosing the location for future energy system in Malaysia.

Assessment of carbon dioxide emission factors from power generation in Burkina Faso

Power generation is the second largest source of greenhouse gases (GHGs), particularly carbon dioxide (CO2), in Burkina Faso's energy sector. When preparing the National Communications on Climate Change, Burkina Faso uses the default emission factors of the Intergovernmental Panel on Climate Change (IPCC) to estimate emissions from power generation. This study presents an assessment of CO2 emission factors from power generation for 2018 in Burkina Faso and an assessment of the contribution of renewable energy to the reduction of CO2 emissions. The national electricity company of Burkina Faso was chosen as the scope for this study. The estimation of emission factors for combustion is based on an analysis of fuels which are characterised in terms of molecular composition, density and water content. For CO2, the emission factor is 76 903 kg/TJ for the combustion of Heavy Fuel Oil (HFO) and 73 525 kg/TJ for that of Distillate Diesel Oil (DDO). Using these emission factors, the CO2 emissions attributable to power generation in 2018 were estimated at almost 580 Gg. The CO2 emission factor for thermal power generation was estimated at 0.663 kg/kWh and that of the electricity generation mix at 0.569 kg/kWh. Finally, the use of 14.25% renewable energy in electricity generation avoided 16.7% of CO2 emissions in 2018. The emission factor of electricity production decreases with the increase in the share of renewable energy in the energy mix.

Renewable energy time series regulation strategy considering grid flexible load and N-1 faults

As the proportion of renewable energy in electricity generation continues to increase, the uncertainty of renewable energy has brought significant challenges to power system security. Traditional renewable energy dispatching methods have less research on power system failure risk analysis due to economic considerations. In this paper, a renewable energy time series regulation strategy considering N-1 faults is proposed to improve the power system economy and security. In this strategy, by researching flexible load aggregation models, the time-series regulation model of aggregation loads is determined. Then the network N-1 security analysis divided into generator detection and branch detection is conducted. Determining possible N-1 faults of the system, the scheme minimizes the operating cost and grid risk. Adopting the methods above, the most desired renewable energy time-series regulation results are obtained. The results have shown that after adopting the proposed strategy in the improved system, the solar and wind curtailment volume is reduced by 38.10%, and the operating cost is reduced by 24.60%. In a daily cycle, the maximum power of all branch power overruns at the most risky moment is reduced by 20.36%, and the sum of the total power of all branch power overruns is reduced by 40.30%.

Transitioning to Clean Energy: A Comprehensive Analysis of Renewable Electricity Generation in the EU-27

The EU power sector is under increasing pressure due to rising electricity demand and the need to meet decarbonisation targets. Member states have been active in investing in renewables and building capacity to increase their share of renewables in electricity generation. However, it is important to examine what progress each member state has made in the deployment of renewable energy for electricity generation and what factors influence gross electricity generation from renewable energy. In this study, logarithmic mean Divisia index (LMDI) analysis was used to examine the changes in EU-27 countries’ gross electricity generation from renewable energy sources (RES), wind, and solar PV from 2012 to 2021. The results show that the RES deployment per capita effect and the RES share effect were the main positive factors for the total gross electricity generation from RES in the EU. In contrast, the RES capacity productivity effect and the energy intensity effect had negative contributions. Population growth had a positive influence but was less significant than the other factors. The deployment of RES per capita effect was the main factor in the overall growth of gross electricity generation from RES in Northern Europe, Central Western Europe, and Central Eastern Europe, according to comparisons between the regional groups. RES share effect was the main driver in Southern Europe. The decrease in RES capacity productivity was the second most important factor influencing the variation in the amount of energy generated by RES in Northern Europe and Central Western Europe. The results could be used to develop more effective and tailored renewable energy policies that take into account the existing main drivers of RES, wind, and solar energy in each of the EU-27 member states.

Standalone Photovoltaic Power Stabilizer Using Double Series Connected Converter in Sudden Cloud Condition

Renewable energy is clean energy that cannot harm the environment in its way, especially on standalone photovoltaic electricity generation. The only problem with renewable energy electricity generation is the intermittency and its instability in power quality and power efficiency. Power system stability in renewable energy is essential during the real environmental case problem such as the sudden cloud. The sudden cloud, known for its ability to decrease solar irradiance input, depends on how thick and big the cloud is. Several attempts had been tried to increase renewable energy power system stability, including modifying its maximum power point tracker with a new algorithm such as perturb and observe. This paper discussed an improved way of maintaining renewable energy power system stability using perturb and observe Algorithm in a double series-connected Converter as the current and power stabilizer. The results show that the current overshoot has decreased by 65,336%, and the current sudden cloud undershoot decreased by 10,529%. Power overshoot also decreased by 43,685%, and the power of sudden cloud undershoot has decreased by 7,133%.

Juxtaposing Sub-Sahara Africa’s energy poverty and renewable energy potential

Recently, the International Energy Agency (IEA) released a comprehensive roadmap for the global energy sector to achieve net-zero emission by 2050. Considering the sizeable share of (Sub-Sahara) Africa in the global population, the attainment of global energy sector net-zero emission is practically impossible without a commitment from African countries. Therefore, it is important to study and analyze feasible/sustainable ways to solve the energy/electricity poverty in Africa. In this paper, the energy poverty in Africa and the high renewable energy (RE) potential are reviewed. Beyond this, the generation of electricity from the abundant RE potential in this region is analyzed in hourly timestep. This study is novel as it proposes a Sub-Sahara Africa (SSA) central grid as one of the fastest/feasible solutions to the energy poverty problem in this region. The integration of a sizeable share of electric vehicles with the proposed central grid is also analyzed. This study aims to determine the RE electricity generation capacities, economic costs, and supply strategies required to balance the projected future electricity demand in SSA. The analysis presented in this study is done considering 2030 and 2040 as the targeted years of implementation. EnergyPLAN simulation program is used to simulate/analyze the generation of electricity for the central grid. The review of the energy poverty in SSA showed that the electricity access of all the countries in this region is less than 100%. The analysis of the proposed central RE grid system is a viable and sustainable option, however, it requires strategic financial planning for its implementation. The cheapest investment cost from all the case scenarios in this study is $298 billion. Considering the use of a single RE technology, wind power systems implementation by 2030 and 2040 are the most feasible options as they have the least economic costs. Overall, the integration of the existing/fossil-fueled power systems with RE technologies for the proposed central grid will be the cheapest/easiest pathway as it requires the least economic costs. While this does not require the integration of storage systems, it will help the SSA countries reduce their electricity sector carbon emission by 56.6% and 61.8% by 2030 and 2040 respectively.

Moving from Linear to Circular Economy in Saudi Arabia: Life-Cycle Assessment on Plastic Waste Management

The discovery of plastic caused a true transformation in human lives and it is used in many essential applications. Despite its significance, humanity struggles to control plastic waste and stop its infiltration into the natural environment. This study aims to review the existing waste management system in Saudi Arabia and evaluate environmental impacts of different plastic waste management scenarios by conducting a life-cycle assessment (LCA). This study covered five scenarios: landfill, incineration with energy recovery, mechanical recycling with incineration of residuals, pyrolysis with incineration of residuals, and combined mechanical recycling and pyrolysis with incineration of residuals. For all scenarios in this study, the CML-IA Baseline method was used, utilizing OpenLCA software. Sources of data for this study were obtained from the Ecoinvent 3.9.1 database and from published peer-reviewed reports. The LCA study revealed that the combined mechanical recycling and pyrolysis with incineration of residuals scenario has the lowest environmental impact. Additionally, the combined scenario can accept a broader range of plastic waste, which improves the overall waste management system towards shifting to circular economy. Therefore, to meet the various recycling requirements, it is recommended to establish a portfolio of plastic waste management techniques in Saudi Arabia to produce high-quality recycled products. It is also recommended to utilize renewable energy for electricity generation in Saudi Arabia, since it was shown in this study that it has a significant positive environmental impact across all impact categories.

Towards realizing vision 2030: Input demand for renewable energy production in Saudi Arabia

Minerals are critical resources in manufacturing and operating renewable energy technologies. Therefore, mineral-producing countries step forward to nestle renewable energy hubs using these resources. Likewise, Saudi Arabia intends to move on an equal footing by designing the national vision 2030 to realize its sustainable development goals. Given this, our objective is to examine the input demand (e.g., mineral production, human capital-augmented labour) for the aggregate renewable energy and solar electricity production within the purview of the decomposed measures of geopolitical risks,' threats' and 'acts' under the Cobb-Douglas production function analysis. To this end, we apply the cross-quantilogram (CQ) technique to examine the causal quantile connectedness between the variables with their fat-tailed distributive feature using monthly data from January 2008 to December 2021. Our findings confirm the increasing return to scale in cumulative renewable energy and solar electricity generation in Saudi Arabia. Specifically, this finding implies that mineral production positively impacts total renewable and solar energy generation at the low and medium quantiles under short, medium and long memories. Also, human capital-augmented labour favourably influences these two clusters of clean energy transitions in all quantiles under entire memories. In addition, the geopolitical risk 'threats' measure elevates, and the 'acts' parameter downsizes these dynamics of energy transformations in whole quantiles. Therefore, we recommend optimizing mineral resources to reach Saudi Arabia's aspirated renewable energy trajectory amid worldwide geopolitical tensions.

Forecasting Development of Green Hydrogen Production Technologies Using Component-Based Learning Curves

Hydrogen energy is expected to become one of the most efficient ways to decarbonize global energy and transportation systems. Green hydrogen production costs are currently high but are likely to decline due to the economy of scale and learning-by-doing effects. The purpose of this paper is to forecast future green hydrogen costs based on the multicomponent learning curves approach. The study investigates the learning curves for the main components in hydrogen value chains: electrolyzers and renewable energy. Our findings estimate the learning rates in the production of PEM and AE electrolyzers as 4%, which is quite conservative compared to other studies. The estimations of learning rates in renewable energy electricity generation range from 14.28 to 14.44% for solar-based and 7.35 to 9.63% for wind-based production. The estimation of the learning rate in green hydrogen production ranges from 4% to 10.2% due to uncertainty in data about the cost structure. The study finds that government support is needed to accelerate electrolysis technology development and achieve decarbonization goals by 2050.

An Environment Perceptive on Solar Installation for University Campus: A Case of Universiti Utara Malaysia

Sustainable energy has become the main agenda globally. Among the renewable energy (RE) sources, solar provides huge potential in electricity production due to the abundance of sun radiation. As tropical country Malaysia enriched with solar radiation the whole year. This paper aimed to study the environmental perspective towards solar installation in the UUM campus building. Climate change sharply decreased by implementing the solar photovoltaic (PV) system up to 91.2 % compared to the conventional source of electricity supply. The global warming impact of solar panel installation was in the range of 44.74 to 178.99 g CO2EQ / kWh. The most contributing process towards this impact was transportation. Installation PV in UUM campus, could avoided carbon dioxide emissions equivalent to 996 ton of waste recycled instead of landfilled or 47583 tree seedlings grown for ten years. Hopefully, the result encourages stakeholders to consume solar power as the primary source of renewable energy components on the way to achieving the Malaysia government’s target of 50% RE in electricity generation.

Promoting renewable energy through national energy legislation

To solve the global warming and energy crisis, substituting fossil fuel energy such as oil with renewable energy is an inevitable trend. International efforts towards this have been great, as evidenced by climate change legislation related to the energy sector. Employing panel data on energy-related legislative activity aimed at climate change in 129 countries in the period 2001–2020, this research statistically investigated the short- and long-term effects of energy laws that promote renewable energy-based electricity generation including non-hydro renewable energy-based electricity generation in the short and long run. The effect is enhanced in countries with a strong legal system. Moreover, the impact of legislative acts is stronger than that of executive orders. Regarding different types of renewable energy resources, the effects of energy laws on solar and wind energy are stronger compared to other renewable sources. Furthermore, heterogeneous tests show that the effect of energy laws on renewable energy is greater in high and upper middle-income countries than in lower middle- and low-income countries. In 2020, the current energy laws increased renewable energy and non-hydro renewable energy electricity generation by 2248.067 and 1888.341 quadrillion kWh, respectively.

Role of economic complexity and energy sector in moving towards sustainability in the exporting economies

The largest contributor to environmental deterioration, the carbon footprint, arises from excessive fossil fuel consumption. Meanwhile, international experts note that despite the positive dynamics in the issue of making commitments to carbon-zero targets, most companies around the globe do not have a clear plan or strategy to achieve environment-based targets. This study addresses sustainable development goals (SDGs) concerning clean energy usage, sustainability, and the environment. Hence, this study investigates the impacts of the economic complexity index (ECI), energy productivity (EPD), renewable energy electricity generation (REEG), and environment-based patents on ecological footprints (ECFP) to attain a carbon-zero environment and SDGs for forty-five exporting countries from 1990 to 2020. An extensive exploration into the connection amongst the explored variables shows that the rises in ECI, EPD, and REEG help subside ECFP in the short-term and long-term estimations. Besides, the results show a bidirectional and unidirectional causality from ECFP to REEG and EPD, respectively. The key practical policies of this work are building modernized tax systems with progressive tax policies, better tax collection, private SDGs financing with incentives regulations, promising project planning on green technologies, and accessibility of grants from global organizations and private sectors to invest in SDGs and a carbon-zero environment target.

Hydrogen Production from Surplus Electricity Generated by an Autonomous Renewable System: Scenario 2040 on Grand Canary Island, Spain

The electrification of final energy uses is a key strategy to reach the desired scenario with zero greenhouse gas emissions. Many of them can be electrified with more or less difficulty, but there is a part that is difficult to electrify at a competitive cost: heavy road transport, maritime and air transport, and some industrial processes are some examples. For this reason, the possibility of using other energy vectors rather than electricity should be explored. Hydrogen can be considered a real alternative, especially considering that this transition should not be carried out immediately because, initially, the electrification would be carried out in those energy uses that are considered most feasible for this conversion. The Canary Islands’ government is making considerable efforts to promote a carbon-free energy mix, starting with renewable energy for electricity generation. Still, in the early–mid 2030s, it will be necessary to substitute heavy transport fossil fuel. For this purpose, HOMER software was used to analyze the feasibility of hydrogen production using surplus electricity produced by the future electricity system. The results of previous research on the optimal generation MIX for Grand Canary Island, based exclusively on renewable sources, were used. This previous research considers three possible scenarios where electricity surplus is in the range of 2.3–4.9 TWh/year. Several optimized scenarios using demand-side management techniques were also studied. Therefore, based on the electricity surpluses of these scenarios, the optimization of hydrogen production and storage systems was carried out, always covering at least the final hydrogen demand of the island. As a result, it is concluded that it would be possible to produce 3.5 × 104 to 7.68 × 104 t of H2/year. In these scenarios, 3.15 × 105 to 6.91 × 105 t of water per year would be required, and there could be a potential production of 2.8 × 105 to 6.14 × 105 t of O2 per year.

Theoretical assessment of the available power from the marine energy sources in Mexico

While the need to use clean, renewable energies in electricity generation is universally understood, Mexico is lagging behind other countries regarding the contribution these sources have to the production of energy nationally. The first hurdle to overcome is providing accurate information for decision-makers and potential investors. In the case of renewable marine energy, this means generating data on the possible installed electrical capacities of the various sources at sites across the country. From this, it is possible to estimate the economic viability of implementing renewable energy projects at specific locations. This work, therefore, aims to characterize the available power from diverse energy sources around the coasts of Mexico and to make recommendations of sites where the energy potential warrants further analysis. A literature review of the power available from marine currents, waves, and thermal and saline gradient sources was performed for the Mexican Caribbean. Several sites were found to be geographically viable; there is sufficient potential energy available to meet at least part of the energy demands of the Yucatan Peninsula and Cozumel Island. Key sites are to the south of Cozumel Island and in the Cozumel Channel for energy harvested from ocean currents. In the northern part of Quintana Roo, sites offer great potential for wave energy, while the central part of the state could be suitable for energy generation from thermal gradients. In Chetumal Bay, there is potential for saline gradient electricity. Wave energy potential was evaluated for the entire Mexican coast, and seven locations are recommended for further investigation. A conservative gross estimation has shown that wave energy could contribute up to 0.2 % of the national demand in the short or mid-term, with a relatively small investment and a low environmental impact.

A Prosumer-Oriented, Interoperable, Modular and Secure Smart Home Energy Management System Architecture

As prices on renewable energy electricity generation and storage technologies decrease, previous standard home energy end-users are also becoming producers (prosumers). Together with the increase of Smart Home automation and the need to manage the energy-related interaction between home energy consumers and Smart Grid through different Demand Response approaches, home energy management becomes a complex and multi-faceted problem, calling for an extensible, interoperable and secure solution. This work proposes a modular architecture for building a Smart Home Energy Management System, integrable with existing Home Automation Systems, that considers the use of standard interfaces for data communication, the implementation of security measures for the integration of the different components, as well as the use of semantic web technologies to integrate knowledge and build on it. Our proposal is finally validated through implementation in one real smart home test-bed, evaluating the system from a functional standpoint to demonstrate its ability to support our goals.

Optimizing the size of the hybrid power and heat generation system during COVID-19 crisis (case study: Italy)

The COVID-19 pandemic has caused more than 2.2 million deaths worldwide. The consequences of this disease are expected to continue. The COVID-19 pandemic has affected the global economy, demand for goods and services, and labor. This deadly virus has affected the energy demand in various sectors, the structure of energy production and especially renewable energy. Although judging the future of renewable energy requires a broader perspective, it is clear that the share of renewable energy in electricity generation, heating and energy policies must change after the COVID-19 pandemic. In this study, the optimal share of energy resources in Italy was calculated using the particle swarm optimization (PSO) algorithm and considering the changes in the energy system, energy demand and prices during the quarantine period.Current conditions and declining fossil fuel prices have led investors to reduce their investment in clean energy, and the amount of investment in renewable energy in 2020 has decreased by about 20% compared to the same period last year. The results of this study show that despite the ubiquitous limitations of COVID-19 for renewable energy, this period is a good opportunity to expand and invest in clean energy due to the increase in the share of electricity demand and domestic heating and the reduction of energy consumption in the industrial sector (Especially solar energy).