A growing concern among investors for social responsibility in relation to the business world and its effect on the environment, society, and government has increased and therefore different types of stock indices and funds that incorporate socially responsible ideals have been developed. However, a literature review revealed that there does not seem to be much information about the volatility of Green Funds or Socially Responsible Investments (SRI). Volatility is an important part of understanding the financial markets and is used by many to understand asset allocation, risk management, option pricing and many other functions. Therefore, the purpose of this thesis is to investigate the volatility performance of SRIs, REFs and Conventional Indices by using different models CAPM, SR, JA and EGARCH, and monthly and daily data from the US, UK, Japan and Eurozone financial markets to compare results.   This thesis has been conducted by following an objective ontological and positivist epistemological position, because the data used for analysis in this thesis is independent from the author and has studied what actually exists, not what the author seeks to interpret. The research approach is functionalist, because this thesis sought to explain how the investments function in relation to volatility comparisons in different financial markets and if this volatility can be predicted through a framework of rules designed by previous researchers. The design is a deductive study of quantitative, longitudinal, secondary data, because hypotheses are derived from theory to test the volatility of time series data between the year 2007 and 2012 through empirical evidence.   Statistical evidence was found to suggest that the EGARCH model for volatility measurement is the best fit to model volatility and daily data can give more information and better consistency between results. SRIs were found to be less volatile than CIs in all financial markets; REFs were found more volatile than CIs in the US and Eurozone markets but not in the UK and Japan markets; REFs were found to be more volatile than SRIs in all markets except the UK; REFs were also found to be more volatile than SRIs and CIs during a recession in all markets except the UK. Evidence also indicated that the correlations between REFs and SRIs in the US and Eurozone were significant, but not significant in the UK and Japan market samples. The correlations were low between the UK and Japan SRIs, Japan and Eurozone SRIs and Japan SRI and Eurozone REF, which suggest that an investor may consider to diversify between these investments. However, all other statistically significant correlations between financial markets were high and could consequentially deliver poor long term investment performance.

In this dissertation I present my approach and findings regarding the development of a simulation model for a small scale renewable energy system. A brief introduction provides the reader with the background as to why there is a need for such a simulation package. The project objectives, research methodology and the research contributions originating from the project is also described. A literature study was done on all the relevant technologies constituting the renewable energy system as well as the techniques required to model the system. A system breakdown identified the various sub modules as well as how they interface with each other. The simulation model was tested by using Alexander bay, South Africa, as a case study. The results obtained from the various modules were discussed and found to correlate with what was expected. Although not contained within the project’s scope, an additional analysis of the effect of the wind data’s resolution on the probable power output of a wind turbine was performed leading to a hypothesis regarding the estimation of a more accurate probable power output extrapolation from data with a coarse resolution. / Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013

The South African Department of Science and Technology is striving to develop a means of producing hydrogen gas in remote and civil areas through the use of renewable energy sources. For the purposes of creating such mobile hydrogen production facilities, a small-scale hydrogen production system based on renewable energy sources needs to be developed and modelled. This system is to serve as a pilot plant for further development of a large scale mobile hydrogen production facility. This work focuses on the characterisation of sizing algorithms for renewable energy sources which can determine component configurations that satisfy power requirements of the system. Additionally, optimal sizing techniques must be developed which can output an optimal plant configuration to a user based on cost and efficiency. To this end, a literature study was done on all the components that make up a renewable energy hydrogen system. The techniques researched were then applied to create algorithms capable of correctly sizing the required components of such a plant. These techniques were integrated into an application created in the LabVIEW environment, which is capable of outputting an optimal plant configuration based on the specific needs of a client. A case study was defined with which the results of the simulation models were verified. Using this work, a future, more comprehensive system may be developed and commercialised, building from the techniques implemented here. / Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013

With electricity tariffs in South Africa escalating at a rapid pace the demand for alternative power sources has increased. One of these renewable energy sources includes the use of biogas. Biogas is not only one of the most efficient and effective renewable energy possibilities available but also requires less capital investment as compared to other renewable sources like hydro, solar and wind and are also more economical as it involves less per unit production cost. Biogas plants have been used around the globe for numerous years, but are a relative new technology in South Africa, predominantly in the red meat industry with the use of slaughter waste as a form of biomass. Slaughter waste offers a vital possible source of renewable energy. A variation of factors makes the production of renewable energy from slaughter waste particularly appealing. The continuous rise of energy prices, waste disposal prices, and incentives for renewable energy production have increased the value of outputs from slaughter waste-to-energy systems. The primary objective of the research is assessing the economic viability of biogas plants at abattoirs in South Africa and if such a biogas plant would be beneficial to an abattoir. The research aimed to determine the viability through various capital budgeting techniques and define what the most significant calculated variables are that should be addressed in such an economic viability model. For the purposes of this study a Class A abattoir with a slaughtering capacity of 400 cattle per day was used as a case study. Biogas will be generated through anaerobic digestion and the utilising of the gas for the generation of electricity and heat by means of a CHP generator. The economic viability study contains of a base case scenario and two other possible scenarios and provides recommendations and a concluding report, based on the scenario that is the most viable. The succeeding techniques which were recognised were used to analyse the economic viability of the biogas plant: Payback Period, Discounted payback period, Net present value, profitability index, and internal rate of return. Furthermore a sensitivity analysis was done in the study with a pessimistic and optimistic outcome on key variables. The study establish that in the base case scenario a positive net present value was realised, the internal rate of return was more than the required rate of return and the payback periods was shorter than required. In this study the concept of biogas plants in the red meat industry were researched with the purpose of determining the economic viability of these plants. In determining the viability of the biogas plant the key variables that will impact the viability was also identified and discussed. Based on the data gathered and assumptions that was made it was concluded that a biogas plant will be beneficial to an abattoir and was considered economically viable. / MBA, North-West University, Potchefstroom Campus, 2014

In this dissertation I present my approach and findings regarding the development of a simulation model for a small scale renewable energy system. A brief introduction provides the reader with the background as to why there is a need for such a simulation package. The project objectives, research methodology and the research contributions originating from the project is also described. A literature study was done on all the relevant technologies constituting the renewable energy system as well as the techniques required to model the system. A system breakdown identified the various sub modules as well as how they interface with each other. The simulation model was tested by using Alexander bay, South Africa, as a case study. The results obtained from the various modules were discussed and found to correlate with what was expected. Although not contained within the project’s scope, an additional analysis of the effect of the wind data’s resolution on the probable power output of a wind turbine was performed leading to a hypothesis regarding the estimation of a more accurate probable power output extrapolation from data with a coarse resolution. / Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013

The South African Department of Science and Technology is striving to develop a means of producing hydrogen gas in remote and civil areas through the use of renewable energy sources. For the purposes of creating such mobile hydrogen production facilities, a small-scale hydrogen production system based on renewable energy sources needs to be developed and modelled. This system is to serve as a pilot plant for further development of a large scale mobile hydrogen production facility. This work focuses on the characterisation of sizing algorithms for renewable energy sources which can determine component configurations that satisfy power requirements of the system. Additionally, optimal sizing techniques must be developed which can output an optimal plant configuration to a user based on cost and efficiency. To this end, a literature study was done on all the components that make up a renewable energy hydrogen system. The techniques researched were then applied to create algorithms capable of correctly sizing the required components of such a plant. These techniques were integrated into an application created in the LabVIEW environment, which is capable of outputting an optimal plant configuration based on the specific needs of a client. A case study was defined with which the results of the simulation models were verified. Using this work, a future, more comprehensive system may be developed and commercialised, building from the techniques implemented here. / Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013

With electricity tariffs in South Africa escalating at a rapid pace the demand for alternative power sources has increased. One of these renewable energy sources includes the use of biogas. Biogas is not only one of the most efficient and effective renewable energy possibilities available but also requires less capital investment as compared to other renewable sources like hydro, solar and wind and are also more economical as it involves less per unit production cost. Biogas plants have been used around the globe for numerous years, but are a relative new technology in South Africa, predominantly in the red meat industry with the use of slaughter waste as a form of biomass. Slaughter waste offers a vital possible source of renewable energy. A variation of factors makes the production of renewable energy from slaughter waste particularly appealing. The continuous rise of energy prices, waste disposal prices, and incentives for renewable energy production have increased the value of outputs from slaughter waste-to-energy systems. The primary objective of the research is assessing the economic viability of biogas plants at abattoirs in South Africa and if such a biogas plant would be beneficial to an abattoir. The research aimed to determine the viability through various capital budgeting techniques and define what the most significant calculated variables are that should be addressed in such an economic viability model. For the purposes of this study a Class A abattoir with a slaughtering capacity of 400 cattle per day was used as a case study. Biogas will be generated through anaerobic digestion and the utilising of the gas for the generation of electricity and heat by means of a CHP generator. The economic viability study contains of a base case scenario and two other possible scenarios and provides recommendations and a concluding report, based on the scenario that is the most viable. The succeeding techniques which were recognised were used to analyse the economic viability of the biogas plant: Payback Period, Discounted payback period, Net present value, profitability index, and internal rate of return. Furthermore a sensitivity analysis was done in the study with a pessimistic and optimistic outcome on key variables. The study establish that in the base case scenario a positive net present value was realised, the internal rate of return was more than the required rate of return and the payback periods was shorter than required. In this study the concept of biogas plants in the red meat industry were researched with the purpose of determining the economic viability of these plants. In determining the viability of the biogas plant the key variables that will impact the viability was also identified and discussed. Based on the data gathered and assumptions that was made it was concluded that a biogas plant will be beneficial to an abattoir and was considered economically viable. / MBA, North-West University, Potchefstroom Campus, 2014

The production of oil requires tremendous amounts of energy consumption through a distributed combustion network of processes along the oil supply chain spectrum. The consequences of fossil-based fuel combustion processes are the generation of Greenhouse Gas (GHG) emissions and hazardous wastewater, which have adverse environmental effects. Potential mitigation options of GHG emissions are the application of renewable and alternative energy sources. This research deals with integrating the upstream oil supply chain with renewable power generation systems in order to assess the impact of energy demand, and CO2 emissions on the efficiency of oil operations and environment . The main focus in this thesis is to evaluate the solar energy alternative for producing part of the energy requirements in the upstream oil supply chain. The output from the research will provide an optimal mix of energy generation in the upstream oil industry in order to comply with CO2 constraints, while sustaining target production plans. An analysis of GHG emission sources and their associated flow rates in the upstream oil supply chain mainly CO2 is discussed in this study. An investigation of replacement of energy supply for some non-critical operations from fossil fuels or other conventional sources to green renewable energy sources mainly from solar energy is also carried out with special focus on enhanced oil recovery operations. An analysis of different types of solar energy and identification of the best type of solar energy technologies that best matches the oil and gas industry is investigated in this study. The thesis will also identify the challenges for solar energy integration including irradiation levels and weather conditions in addition to policy regulations

The energy system in Spain can be characterized as being high energy intensive when compared to the rest of Europe and because of its high dependence on imported resources (around 84%). The focus of this document is to explore a novel approach to describe, as part of this energy system, the electricity system in Spain since 2005 and the economic potential for renewable energy technologies (RET) to replace the electricity generated from fossil resources by 2050. The heart of the design and implementation of any RET policy should be the reduction or elimination of fossil fuel dependency. This document aims at describing the evolution of the Spanish electricity system in the last decade, and addressing the possible influence of certain factors in the design and implementation of the electricity system by using modern modeling technologies to evaluate the potential of RET. This will represent a novel approach to bridge the results from modeling technologies to policy makers. To ensure the credibility and reliability of the data researched, validation criteria has been used which includes the accuracy of information, the content (whether factual or opinion), time (limited to certain periods), format (validity of internet sources, journals, etc), authority (reputable authors and sources), objective reasoning, currency and links to other resources, and the quality of writings and its review among others. The proposed research approach follows a methodology where the first step is to understand the electricity system in Spain, followed by the definition of the model of interest (optimization models) and the design of three different scenarios (Business as Usual, FIT and High fossil prices) for the evaluation of the potential of RET, finishing with the analysis of the results from the model and data collected from the perspectives of what has been done in previous RET policies and plans, and the possible influence of factors such as organizations and corporations on those policies and plans. The results obtained from the model are analysed and compared to the Business as Usual scenario. The amount of electricity generated from fossil resources and to be replaced by RET is calculated using the scenarios, as well as the evolution of primary energy, imports, final energy consumptions and CO2 emissions. In order to test the applicability of this approach, the results of the model have been compared with the current situation of the Spanish electricity system. Calculations using capacity factors of the RET and their share in the current electricity generation are performed in order to identify the final amount of power (MW) to be installed in order to replace the electricity generated (GWh) by fossil resources by 2050. Based on the conclusions, RET has the potential to replace the generation of electricity from fossil fuels but improvements in the efficiency of RET will be needed. In addition, it is recommended that significant considerations in RET policy like the energy and electricity systems should be a strategic component of the Spanish policy system, be done in order to set the Spanish electricity system in a more sustainable path .

In recent decades, interest in placing renewable resources in conventional power systems has increased because of their ability to reduce fossil fuel consumption, which leads to the preservation of the environment. The rapid increase in employing these renewable resource-based DGs drives the system to be more dynamic, and causes many obstacles that need to be overcome. Power system planners and operators should look at the distribution system from another angle, taking into consideration the intermittent behavior of most renewable resources. Furthermore, solid models that are able to handle the uncertainty in generation levels are required. This thesis presents a comprehensive probabilistic model for representing renewable energy resources in long term planning problems. This model utilized large historical data sets, grouping technique, and statistical analysis in order to handle the fluctuations that are caused by the variations in wind speed or solar irradiance. In this research, renewable resources (wind and PV based DGs) ae well as dispatchable units are optimally allocated and sized using a probabilistic optimization model. This model incorporates the intermittent nature of wind speed and solar radiation into the deterministic optimal power flow equations. The variability from the load side and the uncertainty from the feeding side are considered. Genetic algorithm is used in order to minimize the annual energy losses of a distribution system. This thesis proposes a new iterative-based optimization algorithm is proposed in order to determine the minimum number of states that can precisely describe or represent the behavior of wind speed and solar irradiance in operational planning problems. This algorithm is evaluated using a power system planning problem. The proposed algorithm takes into account the annual energy losses and the total DG penetration level and considers them as an indication of how far the proposed method's outcomes are from the actual results. Three di fferent data groupings are applied (hourly, seasonally, and yearly) to investigate the variety of weather and electricity demands on the proposed method. The obtained results should be maintained within an acceptable limit of error which is in this thesis, 2:5%, and any violation of this limit will interrupt the algorithm sequences. The importance of this method actually lies in its ability to reduce the complexity in reliability analysis such that the number of overall system states will be minimized when the analytical evaluation methods are utilized.