Scielo RSS <![CDATA[Journal of Energy in Southern Africa]]> http://www.scielo.org.za/rss.php?pid=1021-447X20190002&lang=en vol. 30 num. 2 lang. en <![CDATA[SciELO Logo]]> http://www.scielo.org.za/img/en/fbpelogp.gif http://www.scielo.org.za <![CDATA[<b>The effect of cetane number and oxygen content in the performance and emissions characteristics of a diesel engine using biodiesel blends</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200001&lng=en&nrm=iso&tlng=en The growth in demand for power generation and energy from alternative fuels at low cost and friendly to the natural environment is increasing. This study used waste plastic pyrolysis oil (WPPO) and ethanol to apply direct blending of conventional diesel, WPPO and ethanol with 2-ethyl hexyl nitrate (EHN). The purpose was to improve the combustion and performance characteristics of the WPPO blends. The EHN has the potential to reduce emissions of carbon dioxide, carbon monoxide, unburnt hydrocarbon, oxides of nitrogen and particulate matter. Ethanol improves viscosity, miscibility, and the oxygen content of WPPO. Five mixing ratios were selected. The mixing ratio with EHN was based on total quantity of blended fuel at 0.01%. At 50% engine load, the brake specific fuel consumption was 0.043 g/kWh compared with CD at 0.04 g/kWh. The blend 90/WPPO5/E5 had the highest value of 14% for brake thermal efficiency, while on NO X emissions three blends 90/WPPO5/E5, 80/WPPO10/E10, 70/WPPO15/E15, had the lowest values of 384 ppm, 395 ppm, 414 ppm, compared with CD fuel at 424 ppm. The implication was that ethanol and WPPO blends can be used in diesel engine power generators as an alternative fuel with modification, as their respective densities of 792 kg/m³ and 825 kg/m³ are close to CD fuel's at 845 kg/m³. Additionally, these combinations with EHN reduced emissions more than earlier thought and improved engine performance, equalling that of conventional diesel fuel. <![CDATA[<b>Positioning South Africa's energy supply mix internationally: Comparative and policy review analysis</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200002&lng=en&nrm=iso&tlng=en Optimisation and diversification of South Africa's energy generation mix is fundamental to meeting its developmental goals and enhancing the crucially important security of supply. South Africa should investigate means to diversify its generating capacity. With the growing demand, South Africa has reached a point where other methods of power generation need to be considered and implemented. This study gives a detailed description of the South African energy supply mix, its evolvement in the past 25 years, and assesses how South Africa fares in comparison with other countries such as its BRICS companions (Brazil, Russia, India, and China) and in the Organisation for Economic Co-operation and Development (OECD), in terms of its current and future energy mix. It was found that the total primary energy supply (TPES) share of non-OECD countries is becoming more prominent, with China, India, and Russia being significant contributors. The OECD's ratio of universal TPES decreased from 1990 to 2015. There is a heavy reliance on fossil fuels in the BRICS countries, which appeals to appropriate policies to influence and guide the transition from the current fossil fuel-dominated energy supply mix to one that follows international trends but, most of all, appreciates its specific geographic position and natural resources. HIGHLIGHTS: • Current South African energy supply mix compared to BRIC and OECD. • Comparison study of the different regions' energy supply mixes. • Global TPES share BRICS, is becoming more prominent. • OECD's share of global TPES has been decreasing. <![CDATA[<b>Introduction of household biogas digesters in rural farming households of the Maluti-a-Phofung municipality, South Africa</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200003&lng=en&nrm=iso&tlng=en The study aimed to introduce biogas as an alternative source of energy for rural cattle farmers in the Maluti-a-Phofung municipality in the Free State Province, South Africa. To augment the rural farming community's adoption of the biodigester technology the following initiatives were undertaken: (i) a situational analysis (or diagnostic survey); (ii) training on biogas production in an integrated crop-livestock-bioenergy system; (iii) installation of the biodigesters; and (iv) monitoring and evaluation of the biogas production. Results on the diagnostic survey showed that the main source of energy for cooking was wood in all the farms and availability of water was not a constraint. Prefabricated biodigesters of 6m³ -12m³ were installed in all the households and, after continual feeding of the units with cattle dung, the production of biogas increased gradually. Monitoring of biogas production showed that, in two-thirds of the households, 80% of their cooking needs were met in summer, while in winter biogas production was minimal due to extremely cold weather. Challenges faced included non-adherence to a feeding regime - resulting in a blockage of the biodigester -and lack of feeding. Generally, farmers in the study area showed a high appreciation of the biodigester technology. <![CDATA[<b>Non-linear multivariate models for estimating global solar radiation received across five cities in South Africa</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200004&lng=en&nrm=iso&tlng=en South Africa continues to lag globally in the adoption of renewable energy systems despite a notable decrease in the cost of applicable renewable energy technologies over the past five years. Most applications of potential solar renewable energy systems are currently in various stages of investigation, leaving this readily accessible resource capacity idle. The present study proposes linear and non-linear analysis of multivariate models for estimating global solar radiation (GSR) received across five cities in South Africa. The significance of this study is to provide effective GSR estimation in the application of solar technologies, while increasing their implementation. The dependency of GSR on meteorological variables such as air temperature, relative humidity and relative sunshine duration was evaluated for January 2007 to June 2018 to realise estimation models for each of the study sites. The Hargreaves-Samani and Angstrom-Prescott empirical models served as the basis for single variable analysis of GSR reliance on each meteorological parameter and their relative variations. The results indicated that the proposed non-linear, multivariate equations perform better than the empirical models as well as linear, single variable regression equations. The suggested models are site-specific and demonstrate a strong correlation to historic GSR values with low, acceptable error indicators. It was also recognised that second- and third-order relationships between the clearness index and multiple meteorological variables provide a more accurate description of GSR for most of the cities under study. These methods are cost-effective, easily accessible and appropriate for the evaluation of the feasibility of solar photovoltaic technologies in South Africa. HIGHLIGHTS: • Unique non-linear, multivariate estimation models for cities in South Africa • Estimation models which can be used in photovoltaic technology implementation <![CDATA[<b>A systematic decision support system to objectively evaluate retrospective energy efficiency modelling options</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200005&lng=en&nrm=iso&tlng=en Tax incentives are one of the methods used by the South African government to incentivise energy efficiency. One of these incentives is Section 12L of the Income Tax Act (1962), which allows a significant tax deduction as a result of quantifiable energy efficiency (EE) savings. The associated EE savings are calculated by means of baseline models and must be in accordance with the national standard for measurement and verification, i.e. SANS 50010, which is based on international practice. The present study developed a methodology that assists EE projects with incentive applications to objectively evaluate potential modelling options and ultimately select a final model. This methodology is based on the weighted sum method. It is verified by applying it to three actual case studies and is further validated by comparing the results obtained from the case studies to independent results of formal and successful incentive applications. The methodology allows for a transparent selection of a modelling option that is compliant with the relevant tax incentive regulatory requirements and untainted by personal bias. <![CDATA[<b>Using normalised cross correlation and variance to determine the source of voltage unbalance exceedances in Eskom networks with wind farms</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200006&lng=en&nrm=iso&tlng=en During an exceedance of the voltage unbalance limit at a busbar there is a need to determine which entity is causing the problem between Eskom, wind farms and other entities that can influence the voltage unbalance at the busbar. There were voltage unbalance limit exceedances at Eskom-K, Eskom-C and Eskom-Z Eskom substations. There was a need to determine which entity was causing the voltage unbalance exceedances at these substations between Eskom, Transnet and wind farms. The normalised cross correlation was used to determine the source of voltage unbalance exceedances at Eskom-K and Eskom-C substation. The normalised cross correlation together with the variance was used to determine the source of voltage unbalance exceedances at Eskom-Z substation. The correlation value of Eskom-K voltage unbalance when correlated with the wind farm's total active power was close to one. The correlation value of Eskom-C voltage unbalance when correlated with the Eskom loads was also close to one. There was a high variance of the voltage unbalance and corresponded to the high variance of the Transnet traction station loads. Based on the correlation and variance results, it was concluded that voltage unbalance at Eskom-K substation was caused by the wind farms. The voltage unbalance at Eskom-C substation was caused by the Eskom loads. The voltage unbalance at Eskom-Z was caused by the traction loads because the Eskom-Z voltage unbalance variance corresponded with the traction load variance. Highlights • Voltage unbalance can be caused by different entities • There is a need to determine which entity is causing the unbalance • Normalised cross correlation can determine the source of unbalance • Use variance or other mathematical tools where correlation fails <![CDATA[<b>Power system inertia in an inverter-dominated network</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200007&lng=en&nrm=iso&tlng=en Erosion of power system inertial energy due to high penetration levels of renewable energy (RE) sources in a power system is a current teething issue with most system operators everywhere. The main issue is displacement of synchronous generators with inverter-based based generators, as the latter do not provide any inertial energy to the power system. The power system thereby becomes vulnerable to large system events (like sudden loss of a big generator or load) and in an inverter-based system this could result in catastrophes such as total collapse of the whole power system due to rapid rate of change of frequency. This paper focuses on power system inertia as RE penetration levels increase and also explores possible mitigation measures such as demand response techniques. <![CDATA[<b>Stress validation of finite element model of a small-scale wind turbine blade</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200008&lng=en&nrm=iso&tlng=en Wind turbine blades are the first mechanical part of a wind turbine that interacts with the wind and hence play a key role in wind power generation. It is important that the wind turbine blade is tested for structural integrity in accordance to design code IEC 61400-23 such as strain limits, fatigue life, blade tip clearance limit, and surface stress. This paper focuses on the calculation and validation of static bending stresses in the blade; it presents the experimental and simulated stress analysis of a small-scale wind turbine blade. The simulation and 3D design software ANSYS, version 19.0 is used in the finite element analysis (FEA). By using FEA, we aim to capture the stress generated on the blade geometry under static loading and unloading conditions. As a first step towards this, the finite element results were validated against experimental results on a kestrel E230i turbine blade. The blade was fixed at one end, loaded, and unloaded statically at three selected points. The finite element results are calculated within a 25% error margin of the experimental results. A reverse engineering procedure was used to determine the appropriate ANSYS model blade properties that were used, as the exact material properties were not available from the manufacturer. HIGHLIGHTS • A single small-scale wind turbine blade is analysed. • Static loading and unloading is experimentally conducted on the blade. • Finite element model simulation is done using ANSYS version 19.0 under similar conditions as in the experiment. • Comparison of result for both analyses was done <![CDATA[<b>Assessing the value of improved variable renewable energy forecasting accuracy in the South African power system</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200009&lng=en&nrm=iso&tlng=en The value associated with an improved variable renewable energy (VRE) forecast has been quantified in this research. The value of improved VRE forecasts can increase with increasing VRE penetration levels as well as the range of this value becoming wider. This value also saturates with high levels of improved VRE forecasts as there is relatively lower impact of improving VRE forecasts further. This paper discusses how the improvement of VRE forecasting could impact the South African power system and representative United States power system jurisdictions. <![CDATA[<b>Potentials of locally manufactured wound-field flux switching wind generator in South Africa</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200010&lng=en&nrm=iso&tlng=en The China-based monopoly of high-energy permanent magnet materials used in modern wind generators impact the economic viability and local content value of most wind turbines installed in South Africa, especially large installations. It is possible to design with less expensive excitation technologies using locally-sourced wound-field electromagnets, which might promote local content. This study involves the optimum design performance comparison of the wound-field flux switching machine (WF-FSM) technology based on two variants - Design I and II (D-I and D-II) - the difference being in the arrangement of their DC wound-field coils. The machines are evaluated using finite element analyses (FEA) with optimum performance emphasised on design parameters such as torque density, efficiency and power factor. The selected design targets are meant to improve the performance to cost fidelity of the proposed wind generator variants. In 2D FEA, D-II can produce up to 18.8% higher torque density (kNm/m³) and 17.1% lesser loss per active volume (kW/m³) than D-I. In 3D FEA, the torque density of D-II remains higher at 10.6%, but its loss per active volume increases by 15% compared to D-I. The discrepancy observed in 2D and 3D FEA is due to an underestimation of the end-winding effects in D-II. The power factor of D-II is higher than D-I, both in 2D and 3D FEA, which may translate to lower kVA ratings and inverter costs. A higher total active mass ensues for the studied WF-FSMs than a conventional direct-drive PMSG, but avoiding rare earth PMs translate to significantly lower costs. Highlights • Two WF-FSM variants - D-I and D-II - are optimally compared in FEA for wind generator applications at medium-scale power level. •D-I displays better loss per active mass while D-II displays better torque density and power factor. • Both WF-FSM variants yield heavier but relatively cheaper wind generators when compared to a conventional PMSG. <![CDATA[<b>Wind capacity factor calculator</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200011&lng=en&nrm=iso&tlng=en The wind capacity factor calculator is developed to perform two main tasks: to estimate the annual energy production from the wind resource at any location in South Africa, and to compare the two datasets used in its operation with standard error analysis to determine whether both datasets are suitable for use. This paper focuses on how the software was developed and on error analysis between the CSIR PV/ wind aggregation study data and the latest Wind Atlas for South Africa data. The results will indicate the way forward after determining whether the error found between the two datasets is significant enough to replace the former with latter, going forward. <![CDATA[<b>Clustering of wind resource data for the South African renewable energy development zones</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200012&lng=en&nrm=iso&tlng=en This study investigates the use of clustering methodologies as a means of reducing spatio-temporal wind speed data into statistically representative classes of temporal profiles for further processing and interpretation. The clustering methodologies are applied to the high-resolution spatio-temporal, meso-scale renewable energy resource dataset produced for Southern Africa by the Council of Scientific and Industrial Research. This large dataset incorporates thousands of coordinates and represents a challenge from a computational perspective. This dataset can be reduced by applying clustering techniques to classify the temporal wind speed profiles into categories with similar statistical properties. Various clustering algorithms are considered, with the view to compare the performances of these algorithms for large wind resource datasets, namely k-means, partitioning around medoids, the clustering large applications algorithm, agglomerative clustering, the divisive analysis algorithm and fuzzy c-means clustering. Two distance measures are considered, namely the Euclidean distance and Pearson correlation distance. The validation metrics evaluated in the investigation includes the silhouette coefficient, the Calinski-Harabasz index and the Dunn index. Case study results are presented for the Komsberg Renewable Energy Development Zone, located in Western Cape, South Africa. This zone is selected based on the high mean wind speed and large standard deviation exhibited by the temporal wind speed profiles associated with the zone. The effects of seasonal variation in the temporal wind speed profiles are considered by partitioning the input dataset in accordance with the low and high demand seasons defined by the Megaflex Time of Use tariff. The clustered wind resource maps produced by the proposed methodology represent a valuable input dataset for further studies such as siting and the optimal geographical allocation of wind generation capacity to reduce the variability and ramping effects that are inherent to wind energy. <![CDATA[<b>Alternatives for small, medium and micro scale enterprises participation in the renewable energy industry - small scale embedded generation review</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-447X2019000200013&lng=en&nrm=iso&tlng=en Over the past decade South Africa has seen an increase in the uptake of solar energy as a result of the Renewable Energy Independent Power Producer Programme, which led to a sharp increase in procurement of utility-scale solar PV projects. On the other hand, the load shedding which was implemented by the national power utility in response to electricity supply and demand challenges resulted in the rise in procurement of small-scale embedded generation solar PV systems. While the REIPPPP has had minimal impact in terms of incorporating small, medium and micro scale enterprises (SMMEs) in the renewable energy value chain, there is a significant opportunity for SMMEs in the small scale embedded generation (SSEG) market segment. This study investigated the challenges and opportunities for SMMEs in SSEG.