The Use of the Technological Innovation Systems Framework to Identify the Critical Factors for a Successful Sustainability Transition to Rooftop Solar in Low-Income Communities within South Africa

South Africa has a large unemployment rate with many households almost completely dependent on social grants for survival. Under such circumstances the potential of rooftop solar in developing vibrant and local energy micro-economies, which can generate and trade in electricity, is highly attractive. In this chapter, it is shown that such systems are uneconomic if considered from the perspective of a private investor. However a different conclusion emerges with respect to public funding. Even without considering the additional benefits of improved health and learning opportunities, lower levels of crime and lower levels of non-payment, rooftop solar becomes an attractive investment for the state, especially in areas of high solar irradiation. The ‘electrification grant’ could be delivered in several ways including the use of a subsidised feed-in-tariff. An initial analysis using the framework of technological innovation systems shows that much of the required structure for a rooftop solar system is already in place. However the state will need to boost efforts to train technicians to install and maintain the infrastructure, accelerate its initiatives to support local manufacture of photovoltaic modules, and strengthen the capability of the science and technology system to support the processes of technology diffusion and adoption

Structured Analysis Reveals Fundamental Mathematical Relationships between Wind and Solar Generations and the United Kingdom Electricity System

The use of wind and solar generation is fundamental to the decarbonisation of the United Kingdom electricity system. However, the optimal level of renewable energy as a proportion of total demand is still being debated. In this paper, several models, whose aims are to predict the efficiency of future system configurations, are explained. The models use historic records from the Gridwatch website for the year 2017, which are then scaled accordingly. The model predictions are first demonstrated for the 2035 Scenario as proposed by the National Grid in FES 2022. The analysis reveals that at least one third of the available wind and solar generation will exceed the ability of the electricity system to use it and will have to be shed. By defining an efficiency measure, the Marginal Decarbonisation Efficiency, which quantifies the incremental extent to which wind generation can decarbonise the electricity system, it is shown that the 2035 Scenario will have a low efficiency. Moreover, it will require the use of combined cycle gas turbines, which is at variants with the predictions of the National Grid steady state model. The paper also describes the derivation of a Generic Model, which allows the level of wind energy and dispatchable generation for all system configurations likely to be encountered in future decades, to be calculated without the use of computer models.Comment: 17 pages, 7 figures, 1 table, unpublished pape

An exploratory study of the South African concentrated solar power sector using the technological innovation systems framework

Abstract: Wide-scale deployment of variable renewable energy (wind and solar photovoltaic) is constrained by its associated requirements for energy storage, the technologies for which are currently too expensive to be routinely used. Concentrated solar power (CSP), with its inherent storage capacity, offers semi-dispatchable electricity at large scale. However, its deployment to date has been restricted by high capital costs and the limited geographical locations with optimal solar radiation to attain required efficiencies. South Africa, with its abundant solar resources, has the potential to develop an export-competitive CSP industry by leveraging existing capabilities in innovation, manufacturing and construction, but has yet to attain this goal. This study applied a qualitative, exploratory approach and the framework of technological innovation systems (TIS) to understand the factors that are currently prohibiting the country from being a global leader in CSP. The assessment has revealed the presence of largely immature TIS, characterised by a heavy reliance on imported technology and market support from the state-supported procurement programme. The advancement of CSP remains contingent on further allocation of CSP procurement targets in this programme and sufficient support to develop entrepreneurial activity. An integrated industrial policy strategy, which can ensure technology transfer and address the high cost of CSP, is recommended as a means of addressing the barriers to its development as a competitive industry

Development of Mathematical Models to Explore the Potential of Wind Fleets to Decarbonize Electricity Grid Systems

Real-time records of energy generation in the UK and Germany have been used to develop models for each country’s electricity generation system, the objective being to provide a means of determining the likely economic limits of wind fleets and their consequent ability to decarbonise their grids. The results from the models, expressed in the form of marginal efficiencies, have then been codified in a pair of simple look-up tables, obviating the need for further reference to the models and providing a simple means of assessing the implications for the grids and their wind fleets of a range of future grid configurations, including increases in wind and solar fleet capacities, anticipated future loss in both countries of nuclear-generating capacity, possible replacement of petrol and diesel passenger vehicles with electric vehicles, and, for the UK only, the conversion of domestic boilers from gas to electricity. It is apparent that headroom, being the difference between annual average grid demand and base generation, is the single most important factor in determining how much wind capacity may be economically deployed in decarbonising grids

The Development of Investment Planning Models for the United Kingdoms Wind and Solar Fleets

Previous work has resulted in the development of an energy model able to calculate wind and solar fleet efficiencies. However, for investment planning purposes, it is necessary to calculate from the lowest economically acceptable efficiencies how much wind and solar generation would be economically justified. The paper explains how this objective has been achieved with arrays (investment planning tables) created after carrying out a structured investigation of the behaviour of the electricity system over the whole of its operational range. The tables are then applied to National Grid prediction of the size and composition of the system in the year 2035. A conclusion is reached that wind and solar generation will only be able to supply about 70% of electrical demand, the other 30% being provided by dispatchable sources of generation, which must be sufficiently fast acting to maintain electricity system stability, such as the use of combined cycle gas turbines. This limit on deployment of wind and solar generation restricts their ability to decarbonise the electricity system and is likely to lead in 2035 to a residual of 72 million tonnes per annum of carbon dioxide emissions which wind and solar generations will be unable to addressComment: 16 pages, 6 figures, 5 table

Efficient and flexible simulation-based sample size determination for clinical trials with multiple design parameters

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of sample size determination problems, often minimising a single parameter (the overall sample size) subject to power being above a target level. We describe a general framework for solving simulation-based sample size determination problems with several design parameters over which to optimise and several conflicting criteria to be minimised. The method is based on an established global optimisation algorithm widely used in the design and analysis of computer experiments, using a non-parametric regression model as an approximation of the true underlying power function. The method is flexible, can be used for almost any problem for which power can be estimated using simulation, and can be implemented using existing statistical software packages. We illustrate its application to a sample size determination problem involving complex clustering structures, two primary endpoints and small sample considerations

Balancing Renewable Energy Capacity, Time of Use Tariffs and Energy Storage in Energy Systems

The intermittency of solar energy predicates the simultaneous use of energy storage to maintain secure supplies. However, storage is expensive to instal and maintain, suggesting that there is an optimum design based on the price tolerance of electricity markets. In this chapter, a method for the calculation of the optimal size of a battery energy storage system (BESS), linked to utility-scale photovoltaic (PV) capacity, is presented. The method, which is illustrated by its application to the South African national grid (GridSA), uses historical generation/demand data to construct a spreadsheet model of the energy system. The model assumes that the difference between base load and energy demand, referred to as headroom, will be met using variable energy sources, including wind, solar, diesel/gas and batteries. Optimal sizing of these components to minimize the use of gas in summer, and make maximum use of low-cost solar and wind, leads to a configuration for GridSA consisting of a 22 GW base load (coal and nuclear), a PV installed capacity of 17.8 GW and a BESS capacity of 3.7 GW/10.4 GWh. A peak time of use tariff of ZAR3,500 per MWh (almost double the average tariff) will be optimal to build an economic case for energy storage as a sustainable option for GridSA