Scielo RSS <![CDATA[Journal of Energy in Southern Africa]]> http://www.scielo.org.za/rss.php?pid=1021-447X20100002&lang=es vol. 21 num. 2 lang. es <![CDATA[SciELO Logo]]> http://www.scielo.org.za/img/en/fbpelogp.gif http://www.scielo.org.za <![CDATA[<b>A techno-economic feasibility study on the use of distributed concentrating solar power generation in Johannesburg</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2010000200001&lng=es&nrm=iso&tlng=es The technical and financial feasibility of small-scale distributed Concentrating Solar Thermal Power (CSP) systems for urban areas in Johannesburg, South Africa, is investigated. The University of the Witwatersrand (Wits), located in central Johannesburg, is used as the basis of a case study for the implementation of these systems. A number of proven CSP technologies were identified and a technology screening was performed to identify suitable technologies for possible implementation, for a reference output of 120 kW(e). From these, a number of systems were chosen for more detailed evaluation and the hourly energy production of these systems was analysed, using local weather data. The Compound Linear Fresnel Reflector system (CLFR) proved to be most suitable because of the space and cost benefits it offers. Systems that integrate organic Rankine cycles (ORC) as well as thermal storage and hybridisation were also investigated. The levelised cost of electricity (LEC) was predicted to be between R4.31 and R3.18 per kWh. Currently these technologies cannot compete financially with the price of local, fossil produced electricity, but with the increase in electricity tariffs and demand for clean reliable power CSP technologies, may become competitive in distributed generation systems in urban areas. <![CDATA[<b>Crude oil price hikes and issues for energy security for Southern Africa</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2010000200002&lng=es&nrm=iso&tlng=es This paper addresses a number of issues related to crude oil prices, focusing on Southern Africa. It begins by analysing oil price movements from 1970 to 2008, and examines various factors that may have contributed to the sharp rise and fall in prices. A characteristic feature in the oil market is the time lags it takes to react to price changes. A high oil intensity of GDP makes the economy vulnerable to oil price increases, so that countries with a high oil/GDP ratio are harder hit than others. There are two main issues for energy security: first, on whether the potential use of the oil weapon can be taken seriously; and second, how to minimize vulnerability to oil supply shocks by reducing oil dependence and by a developing or enlarging a strategic stockpile of oil. <![CDATA[<b>Evaluation of a second order simulation for Sterling engine design and optimisation</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2010000200003&lng=es&nrm=iso&tlng=es This paper reports on the investigation of the simulation accuracy of a second order Stirling cycle simulation tool as developed by Urieli (2001) and improvements thereof against the known performance of the GPU-3 Stirling engine. The objective of this investigation is to establish a simulation tool to perform preliminary engine design and optimisation. The second order formulation under investigation simulates the engine based on the ideal adiabatic cycle, and parasitic losses are only accounted for afterwards. This approach differs from third order formulations that simulate the engine in a coupled manner incorporating non-idealities during cyclic simulation. While the second order approach is less accurate, it holds the advantage that the degradation of the ideal performance due to the various losses is more clearly defined and offers insight into improving engine performance. It is therefore particularly suitable for preliminary design of engines. Two methods to calculate the performance and efficiency of the data obtained from the ideal adia-batic cycle and the parasitic losses were applied, namely the method used by Urieli and a proposed alternative method. These two methods differ essentially in how the regenerator and pumping losses are accounted for. The overall accuracy of the simulations, especially using the proposed alternative method to calculate the different operational variables, proved to be satisfactory. Although significant inaccuracies occurred for some of the operational variables, the simulated trends in general followed the measurements and it is concluded that this second order Stirling cycle simulation tool using the proposed alternative method to calculate the different operational variables is suitable for preliminary engine design and optimisation. <![CDATA[<b>The dilemma of climate information for smallholder farmers</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2010000200004&lng=es&nrm=iso&tlng=es This paper reports on the investigation of the simulation accuracy of a second order Stirling cycle simulation tool as developed by Urieli (2001) and improvements thereof against the known performance of the GPU-3 Stirling engine. The objective of this investigation is to establish a simulation tool to perform preliminary engine design and optimisation. The second order formulation under investigation simulates the engine based on the ideal adiabatic cycle, and parasitic losses are only accounted for afterwards. This approach differs from third order formulations that simulate the engine in a coupled manner incorporating non-idealities during cyclic simulation. While the second order approach is less accurate, it holds the advantage that the degradation of the ideal performance due to the various losses is more clearly defined and offers insight into improving engine performance. It is therefore particularly suitable for preliminary design of engines. Two methods to calculate the performance and efficiency of the data obtained from the ideal adia-batic cycle and the parasitic losses were applied, namely the method used by Urieli and a proposed alternative method. These two methods differ essentially in how the regenerator and pumping losses are accounted for. The overall accuracy of the simulations, especially using the proposed alternative method to calculate the different operational variables, proved to be satisfactory. Although significant inaccuracies occurred for some of the operational variables, the simulated trends in general followed the measurements and it is concluded that this second order Stirling cycle simulation tool using the proposed alternative method to calculate the different operational variables is suitable for preliminary engine design and optimisation.