Regional impervious surface estimation: an urban heat island application

This paper describes a GIS-based estimation method that can be used to forecast future amounts of impervious surface as a mitigation measure for urban heat island effect in a metropolitan region. The method is unique because it employs a regression model that links the existing amount of impervious surface to population and employment at the census tract level. This approach provides a means to forecast future amounts of impervious surface based on projected population and employment. The method also includes a detailed analysis of high-resolution aerial photography to divide impervious surfaces into different categories. Subdividing impervious surfaces is necessary to evaluate potential urban heat island mitigation policies for different types of impervious surface. The analysis here shows that the impervious surface in the metropolitan Atlanta region will increase to 2638 km2 2. “The Albedo is defined as the hemispherical reflectivity averaged over the solar spectrum. A perfect reflector has a = 1, and a perfect absorber has a = 0” (Pomerantz et al. 1999 Pomerantz, M. 1999. Reflective surfaces for cooler buildings and cities. Philosophical magazine B, 79: 1457–1476. [Taylor & Francis Online], [Web of Science ®] [Google Scholar], p. 1458). View all notes in 2030, an increase of 45% from 2000. The most common type of impervious surface is dark-coloured pavement. Within this study area, the analyses showed that two-thirds of impervious surfaces are dark. Replacing dark pavement with light pavement materials, therefore, represents an important opportunity to mitigate the urban heat island effect in the Atlanta region.     

Automated energy management in distributed electricity systems: An EEPOS approach

The increasing capacity of distributed electricity generation brings new challenges in maintaining a high security and quality of electricity supply. New techniques are required for grid support and power balance. The highest potential for these techniques is to be found on the part of the electricity distribution grid.

This article addresses this potential and presents the EEPOS project’s approach to the automated management of flexible electrical loads in neighborhoods. The management goals are (i) maximum utilization of distributed generation in the local grid, (ii) peak load shaving/congestion management, and (iii) reduction of electricity distribution losses. Contribution to the power balance is considered by applying two-tariff pricing for electricity.

The presented approach to energy management is tested in a hypothetical sensitivity analysis of a distribution feeder with 10 households and 10 photovoltaic (PV) plants with an average daily consumption of electricity of 4.54 kWh per household and a peak PV panel output of 0.38 kW per plant. Energy management shows efficient performance at relatively low capacities of flexible load. At a flexible load capacity of 2.5% (of the average daily electricity consumption), PV generation surplus is compensated by 34–100% depending on solar irradiance. Peak load is reduced by 30% on average. The article also presents the load shifting effect on electricity distribution losses and electricity costs for the grid user.     

CFD analysis on the performance of a solar chimney power plant system: Case study in Algeria

The solar chimney power plant (SCPP) is a power generator which uses solar radiation to increase the internal energy of the air circulating in the system, thereby transforming the useful gain of the solar collector into kinetic energy. The produced kinetic energy then can be converted into electrical energy by means of an appropriate turbine. In this paper, four locations in Algeria

(Constantine, Ouargla, Adrar, and Tamanrasset) were considered as case studies to describe the SCPP mechanism in detail. Numerical simulation of an SCPP which has the same geometrical dimensions was performed to estimate the power output of SCPP in these regions. Using the CFD software FLUENT we simulated a two-dimensional axisymmetric model of a SCPP with the standard k-ε turbulence model. The simulation results show that the highest power output produced monthly average value 68–73 KW over the year and the highest hourly power produced in June is around 109–113 KW.     

Higher-efficiency for combined photovoltaic-thermoelectric solar power generation

Solar energy application in a large spectrum has the potential for high-efficiency energy conversion. Though, solar cells can only absorb photon energy of the solar spectrum near their band-gap energy, and the remaining energy will be converted into thermal energy. The use of the thermoelectric generator becomes a necessity for convert this thermal energy dissipated so as to increase efficiency conversion.

This paper analyses the feasibility of photovoltaic-thermoelectric hybrid system and reviews their performance in order to optimize harvested energy. Regarding the thermoelectric effect, a new method of the ambient energy harvesting is presented. This method combines thermoelectric generators and the effects of heat sensitive materials associated to photovoltaic cells in phase change for generating both energy day and night. Experimental measures have been conducted primarily in laboratory conditions for a greater understanding of hybridization phenomena under real conditions and to test the actual performance of devices made. Results show that the hybrid system can generate more power than the simple PV and TEG in environmental conditions. This hybrid technology will highlight the use of renewable energies in the service of the energy production.     

Investigation of the effects of battery types and power management algorithms on drive cycle simulation for a range-extended electric vehicle powertrain

Fuel cell (FC) hybrid vehicle power trains are an attractive technology especially for automotive applications because of their higher efficiency and lower emissions compared to conventional vehicles. This study focuses on the design of an FC hybrid power train system and evaluation of its simulations for a given speed profile through two alternative power management algorithms (PMAs). Parameters suitable for a small vehicle were taken into consideration in the mathematical model of the vehicle. The proposed hybrid power train consists of an energy storage system, composed of a 4-kg battery pack (either lithium-ion (Li-ion) battery, nickel metal hydride, or nickel–cadmium) and a direct methanol fuel cell (DMFC) as the range extender. The PMAs basically aim to fulfill the power requirements of the vehicle and decide how to command the power split between the battery and the FC. The model comprising a DMFC, a battery, and PMAs was developed in MATLAB/Simulink environment. The polarization curve of the FC was obtained using a one-dimensional DMFC model. Vehicle power requirements for a drive cycle were calculated using the equations of longitudinal dynamics of vehicle, and the results were integrated into MATLAB/Simulink model. As a result of the simulations, methanol consumption, state of charge of the battery, and power output of the FC were compared for the PMAs. This comparison shows the effect of PMAs on the hybrid vehicle performance for three battery types. The results indicate that the vehicle range could be increased when proper strategy is used as PMA.     

Flooding and the interannual variability of hydrologic quantities in the Missouri River basin

The six mainstem reservoirs in the Missouri River basin (MRB) are managed mainly to prevent flooding from snowmelt and heavy rainfall, a goal for which the interannual variabilities of precipitation ($P$), evapotranspiration ($\mathit{ET}$), and surface air temperature ($T_{\mathrm{air}}$) are vitally important. We tested the hypothesis that under the expected higher variability owing to global climate change, the months with the highest contributions to the interannual variability of $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ in the MRB will remain unchanged and quantified likely temporal trends in these quantities. Using high-resolution, downscaled Coupled Model Intercomparison Project Phase 5 multi-model ensemble data sets, we compared the multi-year ratio of monthly and annual interannual variability and temporal trends in $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ during 2011–2020 with three future decades. Results showed that the 6 months with the highest interannual variability in $P$ and $\mathit{ET}$ (April–September) are the same in all four decades. However, for $T_{\mathrm{air}}$, only 4 months (December–March) retain their status as highly variable throughout the four decades; September and October variability is exceeded by the variability in other months. This implies that, compared to $P$ and $\mathit{ET}$, the cyclical change in the probabilities of $T_{\mathrm{air}}$ in the MRB is less stable under future global climate change. This finding can be used to consider the need to alter existing strategies for reservoir release while minimizing the likelihood of aggravating flooding below the reservoirs.     

Electricity consumption and economic growth nexus in Zimbabwe revisited: fresh evidence from Maki cointegration

This study explores the relationship between electricity consumption, real gross domestic product per capita and carbon dioxide emissions in Zimbabwe. To achieve this, the study set off by examining the stationarity properties of the variables under review with the Zivot-Andrews (1992 Zivot, E., and D.W.K. Andrews. 1992. Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal Of Business and Economic Statistics 10:251-270. doi: http://dx.doi.org/10.2307/1391541.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) unit root test that accounts for a single structural break. Subsequently, Maki (2012 Maki, Daiki. 2012. “Tests for Cointegration Allowing for an Unknown Number of Breaks.” Economic Modelling 29 (5): 2011–15. https://doi.org/10.1016/J.ECONMOD.2012.04.022 [Google Scholar]) cointegration test, which accounts for multiple structural breaks, is applied for equilibrium relationship between the variables under review while the long run regression of dynamic ordinary least square (DOLS) is employed for long-run coefficients as estimation procedures. In order to account for the direction of causality flow, the Toda-Yamamoto (1995 Toda, H Y.., and Taku Yamamoto. 1995. Statistical inference in vector autoregressions with possibly integrated processes. Journal Of Econometrics 66 (1–2):225–50. doi: 10.1016/0304-4076(94)01616-8.[Crossref], [Web of Science ®] , [Google Scholar]) causality test is used for annual frequency data set spanning from 1971–2014. Empirical evidence from the Maki cointegration test shows that there exists a long-run equilibrium relationship between electricity consumption, carbon dioxide emissions and real gross domestic product per capita over the sampled period. The long-run regression suggests that there exist a positive statistically significant relationship between real income and electricity consumption. Thus, corroborating the electricity-led growth hypothesis. This result is supported by the causality test, as one-way causality is observed running from electricity consumption to real gross domestic product. Thus, this is suggestive to government administrators and policymakers that the Zimbabwean economy is electricity dependent. However, there is a tradeoff for environmental quality. As the increase in electricity consumption increases carbon dioxide emissions. The need for diversification of Zimbabwe energy portfolio to cleaner and environmentally friendly energy sources is recommended, given the world global consciousness for cleaner energy consumption.