Effects of Increased Renewable Energy Consumption on Electricity Prices: Evidence for Six South American Countries

This research examines the relationship between renewable energy consumption and electricity prices in six South American countries (Argentina, Bolivia, Colombia, Chile, Ecuador and Peru). The methodology used is a panel econometric model with annual data for the period 1990–2015. The results show that the consumption of renewable energies influences the price of electricity paid by households, although its influence is very moderate. On the other hand, it was observed that the consumption of renewable energies has no relationship with the energy prices of the industrial sector and the commercial and services sector. In the countries analyzed, an increase in GDP causes an increase in the price of energy in the industrial sector. With more CO2 emissions and a rise in the international price of oil, the annual average price of the industrial sector decreases.

Investing in renewable energies as a strategic option to advance sustainable development in Algeria

This paper aims to highlight the importance of investing in renewable energies in order to advance sustainable development in Algeria, as investment in this field has known continuous development in recent years, convinced that renewable energies are the most important and strategic option for achieving sustainable development in the future, and has been reached To a set of results, the most important of which are that renewable energy has the ability to meet the need for development in Algeria, as well as its ability to increase development and growth on a large scale, and renewable energy plays an important role in translating the dimensions of sustainable development, as its development projects contribute to achieving Economic gains, improve social conditions and preserve the environmental heritage for future generations, in order to achieve sustainable development.

Ferrites and Nanocrystalline Alloys Applied to DC–DC Converters for Renewable Energies

The medium frequency transformer (MFT) with nanocrystalline alloys is quintessential in new DC–DC converters involved in various front-end applications. The center piece to achieve high-performance, efficient MFTs is the core. There are various options of core materials; however, no deep information is available about which material characteristics and design procedure combo are best to get high performance MFTs while operating at maximal power density. To provide new insights about interrelation between the selection of the core material with the compliance technical specifications, differently to other proposals, this research work aims to design and build, with the same methodology, two MFT prototypes at 20 kHz, with nanocrystalline and ferrite cores, to highlight power density, and overall performance and cost, as matching design criteria. As the experimental results show, a nanocrystalline core has the highest power density (36.91 kW/L), designed at 0.8 T to obtain low losses at 20 kHz, achieving an efficiency of 99.7%. The power density in the ferrite MFT is 56.4% lower than in the nanocrystalline MFT. However, regarding construction cost, the ferrite MFT is 46% lower, providing this a trend towards low-cost DC–DC converters. Finally, high power density in MFTs increases the power density of power DC–DC converters, which have relevant applications in fuel cell-supplied systems, renewable energies, electric vehicles, and solid-state transformers.

Modeling of Risk Aversion Linked to Renewable Energy Policy and Decision-Maker Behavior

This paper presents the behavior of decision makers, the possible choices and the strategies 1 resulting from the uncertainties related to the integration of renewable energies. Its uncertainties 2 are the risks associated with the volatility of renewable sources, the dynamics of energy production 3 as well as the planning and operation of the electricity grid. The goal is to model the risk-averse 4 decision-maker’s behavior and the choice of integrating renewable energies into the electrical system. 5 Following a bibliographic approach, we expose a methodology to model the decision-maker’s 6 behavior(risk aversion and predilection for risk) to risk taking. The risk-averse decision maker may 7 adopt nonlinear utility functions. Risk aversion is a behavior that reflects the desire to avoid risk 8 decisions and thus reduces the risk of adverse consequences. A decision support tool is provided to 9 the decision-maker to choose a best-fit strategy based on his preferences. The rational and risk-averse 10 decision-maker would seek to maximize a concave utility function instead of seeking to minimize its 11 cost. Taste or aversion to risk can be modeled by a thematic function of utility.

Operation of the Egyptian Power Grid with Maximum Penetration Level of Renewable Energies Using Corona Virus Optimization Algorithm

Countries around the world are looking forward to fully sustainable energy by the middle of the century to meet Paris climate agreement goals. This paper presents a novel algorithm to optimally operate the Egyptian grid with maximum renewable power generation, minimum voltage deviation and minimum power losses. The optimal operation is performed using Corona Virus Algorithm (CVO). The proposed CVO is compared to the Teaching and Learning-Based Optimization (TLBO) algorithm in terms of voltage deviation, power losses and share of renewable energies. The real demand, solar irradiance and wind speed in typical winter and summer days are considered. The 2020 Egyptian grid model is developed, simulated, and optimized using DIgSILENT software application. The results have proved the effectiveness of the proposed CVO, compared to the TLBO, to operate the grid with the highest share possible of renewables. The paper is a step forward to achieve Egyptian government targets to reach 20% and 42% penetration level of renewable energies by 2022 and 2035, respectively.

Comparison of Nature and Synthetic Zeolite for Waste Battery Electrolyte Treatment in Fixed-Bed Adsorption Column

To support a sustainable energy development, CO2 reduction for carbon neutralization and water-splitting for hydrogen economy are two feasible technical routes, both of which require a significant input of renewable energies. To efficiently store renewable energies, secondary batteries will be applied in great quantity, so that a considerable amount of energy needs to be invested to eliminate the waste battery electrolyte pollution caused by heavy metals including Cu2+, Zn2+ and Pb2+. To reduce this energy consumption, the removal behaviors of these ions by using clinoptilolite and zeolite A under 5, 7 and 10 BV h−1 in a fixed-bed reactor were investigated. The used zeolites were then regenerated by a novel NH4Cl solution soaking, coupled with the ultrasonication method. Further characterizations were carried out using scanning electron microscopy, N2 adsorption and desorption test, and wide-angle X-ray diffraction. The adsorption breakthrough curves revealed that the leaching preference of clinoptilolite was Pb2+ > Cu2+ > Zn2+, while the removal sequence for zeolite A was Zn2+ > Cu2+ > Pb2+. The maximum removal percentage of Zn2+ ions for clinoptilolite under 5 BV h−1 was 21.55%, while it was 83.45% for zeolite A. The leaching ability difference was also discussed combining with the characterization results. The fact that unit cell stayed the same before and after the regeneration treatment approved the efficacy of the regeneration method, which detached most of the ions while doing little change to both morphology and crystallinity of the zeolites. By evaluating the pH and conductivity changes, the leaching mechanisms by adsorption and ion exchange were further studied.