Research Assistant and Senior Collaborator, Laboratory for Interdisciplinary Statistical Analysis, Department of Statistics, University of Ibadan
Modelling Determinants of Renewable Energy Consumption In Africa
The research aim to examine factors or determinants of renewable energy consumption among Africa nations. Renewable energy resources are spread over wide geographical areas in contrast to other energy sources which are available only in isolated locations. Partly for this reason, renewable energy options have become very attractive and have become very important component of the world energy consumption. The study employed Bayesian Model Averaging (BMA) procedures to account for the uncertainty associated model choice and variable selection. We were able to establish country by country determinants and identify the major renewable energy determinants in Africa.
Abstract: The impact of consumption of renewable energy on CO2 emissions was investigated, in five MERCOSUR’s countries from 1980 to 2014. The autoregressive distributed lag (ARDL) in the form of Unrestricted Error Correction Model to decompose the total effect of variables into it is the short- and long-run components. The results of preliminary tests showed the presence of cross-sectional dependence between the variables, the stationarity of all variables in the first differences, and the homogeneity in panel data. Moreover, the specification tests pointed to the presence of cross-sectional dependence, non-correlation between the crosses, serial correlation in the panel data model, and the existence of heteroskedasticity. The results of semi-elasticities (short run) and elasticities (long run) of ARDL model pointed that the economic growth and consumption of fossil fuels increase the CO2 emissions in the short and long run, while the consumption of renewable energy reduces them. Despite the consumption of renewable energy reducing the environmental degradation in the MERCOSUR countries, its impact is small. Finally, this study proved that the consumption of renewable energy is able to reduce the CO2 emissions, which is responsible for the environmental degradation in the MERCOSUR countries, and that the economic growth of these same countries increases the CO2 emissions, along with the fact that all MERCOSUR countries are highly dependent of fossil fuels.
Pub.: 23 Jan '18, Pinned: 26 Apr '18
Abstract: Publication date: 15 April 2018 Source:Applied Energy, Volume 216 Author(s): Hafthor Ægir Sigurjonsson, Lasse R. Clausen The Danish energy system will continue to evolve in the years ahead as the goal is to be independent of fossil fuels by 2050. This introduces several challenges in dealing with intermittent energy sources, such as wind and solar. A novel biomass-based polygeneration system concept is proposed, which can offer certain solutions to these challenges. The main concept is storing electricity by producing bio-SNG from syngas generated by biomass gasification and electrolytic hydrogen when electricity prices are low, and producing electricity when prices are high. The analytical framework is built on thermodynamic modeling, and techno-economic analysis is applied to determine the total revenues required and net present value, given a range of bio-SNG and electricity prices. The marginal cost of operation is then used to estimate the average operation time in each production mode. The results demonstrate that both electricity (46%) and bio-SNG (69%) production efficiencies are high. If district heating is coproduced, the total efficiencies increase to 85% and 90%, respectively. Furthermore, it was found that the annual operation time in each mode varies significantly depending on the future electricity price scenario and bio-SNG price. A system that can select the production or consumption of electricity depending on the market price enables constant operation all year round. This results in a higher net present value for the system and may lead to a positive return on investment, given the appropriate market price of electricity and bio-SNG. However, the techno-economic analysis revealed that the district heating product may be important for the economic feasibility of the polygeneration plant. This system may offer solutions in a smart energy system connecting electrofuel, heat, and power production, toward a 100% renewable system. Graphical abstract
Pub.: 26 Feb '18, Pinned: 26 Apr '18
Abstract: Publication date: Available online 16 February 2018 Source:Computers & Chemical Engineering Author(s): Siyuan Chen, Zheng Guo, Pei Liu, Zheng Li Increasing global energy consumption and consequent greenhouse gas emissions pose great challenges to the sustainable development of international human society. Electricity constitutes the largest part of energy carriers, and the power sector is identified as the key sector with great carbon dioxide mitigation potential. Therefore, power generation expansion planning (GEP) problem has drawn great attention due to its important role in global energy supply, renewable energy utilization and carbon dioxide mitigation. Several important issues, including renewable energy sources integration, operating reserve, deregulated power market, demand response and carbon pricing mechanism should be incorporated in a GEP problem. Energy system engineering provides a methodological framework to address the complex energy, economic and environmental problems by adopting an integrated systematic approach, featuring superstructure-based modeling, mixed-integer programming, multi-objective optimization, and optimization under uncertainty. Recent advances of these approaches in GEP problems related to the five issues mentioned above are reviewed and discussed in this article.
Pub.: 26 Feb '18, Pinned: 26 Apr '18
Abstract: Publication date: March 2018 Source:Control Engineering Practice, Volume 72 Author(s): Maria Pia Fanti, Agostino Marcello Mangini, Michele Roccotelli This paper deals with the energy consumption management problem in buildings by modeling and controlling the main electric appliances. Renewable energies are taken into account by considering the production schedules of both wind and solar sources. Each appliance is described by modular mathematical models by means of the Matlab/Simulink software. A simulator is designed that models the load energy consumptions and helps to recognize how they contribute to peak demand. Moreover, a controller to manage the load usage is designed in a Petri Net framework. In the proposed control strategy, the comfort conditions are respected for each appliances on the basis of the user preferences. Finally, a real case study validates and tests the effectiveness of the simulator applied to the considered appliances.
Pub.: 10 Jan '18, Pinned: 26 Apr '18