Journal of Energy in Southern Africa最新文献

{"title":"Assessing the value of improved variable renewable energy forecasting accuracy in the South African power system","authors":"Jarrad Wright, G. Landwehr, E. Chartan","doi":"10.17159/2413-3051/2019/V30I2A6293","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6293","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73453529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction of household biogas digesters in rural farming households of the Maluti-a-Phofung municipality, South Africa","authors":"K. M. Nape, P. Magama, M. Moeletsi, Mphethe I. Tongwane, P. M. Nakana, V. Mliswa, M. Motsepe, S. Madikiza","doi":"10.17159/2413-3051/2019/V30I2A5885","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A5885","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82269327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using normalised cross correlation and variance to determine the source of voltage unbalance exceedances in Eskom networks with wind farms","authors":"N. Ntsadu","doi":"10.17159/2413-3051/2019/V30I2A5658","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A5658","url":null,"abstract":"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 normal- ised 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 un- balance 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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81017461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Positioning South Africa's energy supply mix internationally: Comparative and policy review analysis","authors":"Vanessa Ndlovu, R. Inglesi‐Lotz","doi":"10.17159/2413-3051/2019/V30I2A5409","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A5409","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"514 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77845633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potentials of locally manufactured wound-field flux switching wind generator in South Africa","authors":"U. B. Akuru, M. Kamper","doi":"10.17159/2413-3051/2019/V30I2A6315","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6315","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84994979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stress validation of finite element model of a small-scale wind turbine blade","authors":"Tolulope Babawarun, W. Ho, H. Ngwangwa","doi":"10.17159/2413-3051/2019/V30I2A6355","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6355","url":null,"abstract":"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 aims to focus 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 wind turbine 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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90322670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wind capacity factor calculator","authors":"H. Kekana, G. Landwehr","doi":"10.17159/2413-3051/2019/V30I2A6451","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6451","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"112 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79351936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clustering of wind resource data for the South African renewable energy development zones","authors":"Chantelle Y. Janse van Vuuren, H. Vermeulen","doi":"10.17159/2413-3051/2019/V30I2A6316","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6316","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"125 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86063926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power system inertia in an inverter-dominated network","authors":"Mpeli J Rampokanyo, Pamela Ijumba-Kamera","doi":"10.17159/2413-3051/2019/V30I2A6341","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A6341","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82458063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic decision support system to objectively evaluate retrospective energy efficiency modelling options","authors":"L. Botes, W. Booysen, M. Mathews, M. Kleingeld","doi":"10.17159/2413-3051/2019/V30I2A5740","DOIUrl":"https://doi.org/10.17159/2413-3051/2019/V30I2A5740","url":null,"abstract":"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.","PeriodicalId":15666,"journal":{"name":"Journal of Energy in Southern Africa","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75164814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}